Week 2026-W18

Research Scientist role focused on building multimodal foundation models and systems for humanoid robots and embodied agents, involving algorithm design, large-scale training/inference, and deployment on physical hardware and simulations.

Senior Deep Learning Researcher at NVIDIA focusing on diffusion-based technologies and multi-modal learning. The role involves inventing and building new techniques, combining diffusion models with LLMs, and publishing research findings. It requires a PhD, research experience, and a strong publication record in leading AI conferences and journals.

Senior Research Scientist focused on fundamental generative AI research, particularly for biomolecular design and scientific applications. The role involves designing and implementing novel, large-scale generative models, publishing research, and transferring technology to product groups.

AI Research Scientist at NVIDIA focusing on developing and optimizing GPU-accelerated generative AI models for language, vision, and robotics, with a strong emphasis on publishing research and transferring technology to products.

Research Scientist role focused on fundamental generative AI research, pushing boundaries in image, video, 3D, or scientific applications. Requires a strong mathematical foundation, novel model development, and publication in top ML venues. The role involves designing and implementing large-scale generative AI methods, publishing original research, and collaborating with research and product teams.

Research Scientist role focused on fundamental generative AI research, particularly for scientific applications like biomolecular design. The role involves developing novel, large-scale generative models, publishing research, and potentially transferring technology to product groups. Requires a strong theoretical and practical understanding of generative AI and deep learning.

PhD research intern focused on advancing LLMs using reinforcement learning. Will design, implement, and evaluate new RL-based methods for improving LLM behavior, reasoning, alignment, and task performance. Involves hands-on experimentation and large-scale GPU cluster work.

AI Research Scientist at NVIDIA focusing on developing and optimizing GPU-accelerated generative AI models for language, vision, and robotics, with a strong emphasis on publishing research and transferring technology to products.

NVIDIA Research Singapore is seeking AI researchers to develop and optimize GPU-accelerated efficient AI computing for language models, visual generation, and robotics, focusing on pushing generative AI boundaries and publishing research.

NVIDIA is seeking a Senior AI Engineer to work on world foundation models for generating dynamic worlds, focusing on human appearance, motion, and action understanding. The role involves applied research, developing and validating model improvements, and hardening them into production-grade checkpoints. Responsibilities include researching architecture changes, exploring multimodal modeling, improving training/inference efficiency, defining training objectives, developing benchmarks, and translating research into robust implementations. Requires a PhD or equivalent experience, 8+ years of applied research/industry experience, 3+ years in generative models for image/video/audio, proficiency in Python, PyTorch, C++, CUDA, and experience with large model training and inference optimization.

Senior Research Scientist focused on AI-Mediated Reality and Interaction, creating interactive physical AIs for dynamic 4D worlds. Research areas include AI, neural rendering, graphics, generative modeling, LLMs, and human behavior. The role involves proposing and prototyping novel research, publishing in top venues, collaborating with teams, creating demonstrations, and participating in technology transfer to products like Isaac, Omniverse, and Metropolis.

Senior Software Engineer focused on building and optimizing AI inference systems for large-scale models, involving GPU kernel optimization, inference framework development (vLLM), benchmarking (MLPerf), and orchestration of distributed deployments.

Senior Machine Learning Engineer at NVIDIA focused on building, training, and deploying large-scale end-to-end autonomous driving models using VLM/VLA architectures and a data flywheel for continuous improvement. The role involves designing models, driving data collection and iteration, curating multimodal datasets, developing data-centric algorithms, exploring new data sources, and creating agentic data workflows.

NVIDIA is seeking a Solutions Architect with deep expertise in Generative AI (LLM) model building, focusing on training LLMs at scale and customizing them. This role involves designing solutions, leading workshops, and collaborating with internal teams to build full-stack GenAI solutions for enterprise use cases. The position requires significant experience in deep learning and generative AI, with an emphasis on large-scale LLM training.

Product Manager for NVIDIA's Agentic AI Platform, focusing on AI agents that generate, optimize, and deploy GPU kernels. The role involves defining product strategy, roadmaps, and end-to-end product lifecycles, from data generation and evaluation to deployment and continuous improvement, in collaboration with engineering, research, and customers.

NVIDIA's Cosmos team is seeking an ML and Agentic Systems Engineer to build AI-native systems and agentic workflows across the ML lifecycle. The role focuses on creating the meta-layer for ML development, enabling AI agents to interact with code, data, experiments, and evaluations to accelerate ML processes. Responsibilities include designing agentic workflows, building AI-native systems, creating self-improving loops, owning large-scale Python/PyTorch codebases, and scaling evaluation platforms.

Senior Software Engineer role focused on building and scaling agentic AI systems for high-performance code generation. Responsibilities include architecting agentic systems, scaling distributed systems, developing evaluation frameworks, optimizing for performance on NVIDIA GPUs, and establishing engineering standards. Requires experience in building coding agents, AI evaluation, and distributed systems.

NVIDIA is seeking a Principal Engineer to lead performance analysis and optimization of large-scale AI training and post-training workloads on NVIDIA's hardware and software stack. The role involves deep technical analysis across compute, memory, communication, and frameworks to improve efficiency and influence future roadmaps.

Senior Software Engineer focused on building and optimizing AI inference systems, including vLLM, GPU kernels, and orchestration for large-scale model deployments. The role involves performance engineering, benchmarking (MLPerf), and potentially research integration.

Senior Solutions Architect specializing in Generative AI, focusing on training LLMs, fine-tuning, and RAG implementation. The role involves architecting end-to-end solutions, collaborating with customers and sales teams, and providing technical leadership for LLM training and Agentic AI workflows on NVIDIA platforms.

Research Scientist role focused on 3D computer vision and deep learning, involving novel technique research, publication, and collaboration. Requires a Ph.D. and a strong publication record in top venues.

NVIDIA is seeking a PhD student for joint research at Bar-Ilan University on next-generation Foundation Models for Materials Science. The role involves developing novel multi-modal foundation models, leveraging large-scale data, representation learning, and uncertainty estimation, with a focus on publishing results in top-tier venues.

Senior Deep Learning Software Engineer to design and build an automated inference and deployment solution with a scalable architecture focusing on ease-of-use and compute efficiency. The role involves developing features in high-level frameworks, implementing a high-performance execution environment, and low-level GPU optimizations.

NVIDIA is seeking a Senior Applied Researcher to build and deploy end-to-end agentic systems that integrate LLMs with domain tools to enhance NVIDIA's products, specifically targeting HW and SW engineering workflows. The role involves developing complex agentic systems with multi-agent coordination, long-horizon reasoning, planning frameworks, and RAG pipelines, and establishing evaluation backbones for iteration and improvement.

Machine Learning Engineer focused on humanoid robotics, developing and advancing foundation models (GR00T, Cosmos) for loco-manipulation, and implementing algorithms for real-world robot deployment. The role involves robot learning, synthetic data generation, and sim-to-real transfer.

NVIDIA is seeking an LLM Reinforcement Learning Framework Engineer to develop and deploy RL algorithms for LLM post-training, focusing on improving reasoning and alignment. The role involves integrating RL components into NVIDIA's LLM stack, crafting experiments, and ensuring production readiness. Requires strong Python, PyTorch, and practical RL experience with LLMs, along with familiarity in async/distributed orchestration.

Manager for a Deep Learning Engineering team focused on delivering production-quality deep learning solutions for autonomous vehicles and robotics on edge hardware. The role involves leading a team, defining technical initiatives, and collaborating with automotive OEMs and robotics partners to optimize solutions on NVIDIA platforms, working at the intersection of model architectures, compiler technology, and embedded deployment.

Research Scientist role focused on 3D computer vision and deep learning for scene understanding, pose estimation, and localization. The role involves publishing original research, mentoring, and collaborating with productization teams. Requires a Ph.D. and a strong publication record in top computer vision venues.

Senior Deep Learning Algorithms Engineer at NVIDIA to optimize biology and structural biology models (LLMs, VLMs) for inference performance on GPUs using TensorRT-LLM and related stacks. Focus on low-latency, high-throughput inference, quantization, custom GPU kernels, and production deployment.

Research Scientist role focused on developing new deep learning models for code and mathematics reasoning, designing large-scale training algorithms, and open-sourcing models using NeMo. The role involves publishing research papers and collaborating with academic labs.

Senior Deep Learning Software Engineer focused on optimizing LLM inference performance on NVIDIA accelerators using frameworks like TensorRT LLM, VLLM, and Triton. The role involves implementing and scaling inference, serving, and deployment algorithms, collaborating with various teams, and contributing to NVIDIA/OSS LLM frameworks.

Senior Solutions Architect specializing in Generative AI, focusing on developing end-to-end AI solutions, reference architectures, and proof-of-concept engagements for agentic AI systems and LLM-powered workflows. The role involves designing multi-cloud strategies, leading workshops, and advising on MLOps principles and emerging standards for agentic AI.

Senior ML Engineer focused on building and optimizing large-scale Reinforcement Learning (RL) training frameworks for multi-modal Autonomous Vehicle (AV) foundation models. This role involves designing simulation and data processing pipelines, refining reward functions, and ensuring the reliability of training workflows on GPU clusters, with a focus on closed-loop simulation for training end-to-end AV models.

NVIDIA is seeking an AI Engineer or Solutions Architect to enable ecosystem partners for Generative AI. The role involves building innovative proof-of-concept solutions and reference architectures for AI agents, demonstrating NVIDIA's full-stack accelerated Generative AI platforms. Responsibilities include acting as a technical expert, developing foundational solutions, providing technical blueprints, advising on deployment, and enabling partners to build their own services and products. The role requires experience in deploying AI models at scale, building enterprise-grade agentic AI systems, and proficiency in LLM/VLM frameworks and Python/C++.

Senior Software Engineer focused on optimizing and contributing to open-source LLM inference serving engines like vLLM and SGLang to run efficiently on NVIDIA GPUs, focusing on high-throughput, low-latency inference at scale.

Senior Software Engineer to join the AI Blueprints team to build multimodal, scalable, production-grade reference RAG solutions using Agentic AI and NVIDIA Nemotron models. Develop orchestration layers to dynamically interact with proprietary unstructured and structured data sources. The role involves planning, building, and refining RAG workflows, designing and implementing AI agents for reasoning, planning, and multi-step execution, running POCs, hardening patterns, building and deploying end-to-end RAG pipelines using microservices architecture, and driving continuous improvement through evaluation and performance analysis.

Research Scientist role focused on Generative AI for Physical AI, developing advanced video generative and video-language models, and scaling large-scale training systems for foundation models. Requires a PhD and expertise in PyTorch, diffusion, vision-language, reasoning models, RL, and physics simulation.

NVIDIA is seeking an Inference Optimization Architect to accelerate and scale Speech AI models, focusing on reducing inference latency, improving throughput, and optimizing resource utilization across AI infrastructure. The role involves implementing model compression techniques, developing custom kernels, designing serving infrastructure, and optimizing inference across diverse GPU platforms.

Senior Director role focused on defining and executing a comprehensive data strategy for foundation models, encompassing multi-modal data acquisition, curation, synthetic generation, and alignment techniques like RLHF. This role bridges research insights with data collection to improve model performance and safety, and engages with customers to translate deployment gaps into data priorities.

Senior Software Engineer role focused on developing and researching agentic memory systems, including designing benchmarks, generating synthetic data, running experiments, and contributing to open-source evaluation tools. The role involves partnering with other NVIDIA teams deploying agents and advancing the state of the art in agentic memory evaluation.

NVIDIA is seeking a Senior Machine Learning Engineer for their autonomous driving perception team. The role involves designing and developing end-to-end deep learning solutions for perception modules, focusing on road layout detection and other critical driving components. Responsibilities include applied research, data-driven development, and productizing solutions with a focus on safety, latency, and robustness. Experience with deep learning frameworks, Python/C++, and perception for autonomous driving or robotics is required.

NVIDIA is seeking an experienced Senior High-Performance LLM Training Engineer to optimize LLM training workloads on advanced computing systems. The role focuses on improving the efficiency of NVIDIA's high-performance LLM software stack using frameworks like PyTorch and JAX for training on thousands of GPUs, and influencing future hardware roadmaps.

Senior Solutions Architect specializing in Generative AI, focusing on building and architecting enterprise-grade agentic AI systems, RAG pipelines, and multi-modal workflows. The role involves leading prototyping, proof-of-concept collaborations, and providing technical advisory to sophisticated AI partners, with a strong emphasis on GPU-accelerated inference at scale, production optimization, and creating reusable technical assets. Responsibilities include problem-solving across the AI stack, collaborating with internal teams, and contributing to team growth and practice building.

Solutions Architect focused on enabling partners to build, benchmark, fine-tune, optimize, and deploy foundation model solutions for customer workloads, with an emphasis on reasoning, multimodal, and production inference.

Solutions Architect focused on enabling partners to build, benchmark, fine-tune, optimize, and deploy foundation model solutions for customer workloads, with a strong emphasis on production inference and reasoning/multimodal models.

Senior Solutions Architect specializing in Generative AI, focusing on building and deploying enterprise-grade agentic AI systems, RAG pipelines, and multi-modal workflows with GPU-accelerated inference at scale. The role involves acting as a technical advisor, leading prototyping, architecting solutions, and resolving complex system issues for NVIDIA's advanced AI partners.

NVIDIA is seeking a Deep Learning Solution Architect to drive the research, development, and optimization of Reinforcement Learning algorithms and infrastructure for LLMs and multimodal models. The role involves collaborating with internal teams, improving customer engagements with NVIDIA RL technologies, and developing toolchains and documentation. Requires MS/PhD, 5+ years of experience in RL, LLM training, or multimodal learning, proficiency in PyTorch, and strong engineering skills in distributed training or orchestration.

NVIDIA is seeking a Deep Learning Software Engineer to analyze and improve the performance of their inference ecosystem, focusing on TensorRT and related frameworks. The role involves optimizing inference solutions for various NVIDIA accelerators, developing new model pipelines, and collaborating with cross-functional teams on generative AI, robotics, and vision/speech understanding applications.

NVIDIA is seeking a Deep Learning Solution Architect to design and optimize production-grade generative AI solutions for enterprise customers, focusing on LLM training, RAG, and agentic inference using NVIDIA's ecosystem.

Senior Deep Learning Engineer at NVIDIA to optimize and deploy foundation models for physical AI applications (AVs, robots, video analytics) on GPU platforms, focusing on high-performance inference.

Senior Applied Scientist/AI Engineer at NVIDIA focusing on Sovereign AI efforts. The role involves end-to-end model training (pre-training, CPT, SFT, alignment), rigorous evaluation and benchmarking, and inference optimization using tools like TensorRT-LLM and NIM. Requires strong Python, PyTorch, and experience with large-scale ML frameworks.

NVIDIA is looking for a Deep Learning Senior Engineer to design, implement, and deploy end-to-end autonomous driving systems. The role focuses on leveraging LLMs, VLMs, and VLAs for reasoning and planning, involving model training, pre-training, fine-tuning, and integration into safety-critical vehicle firmware. Experience with production-grade ML models and C++ for deployment is required.

Manager for Large Language Model Inference at NVIDIA, focusing on developing and optimizing LLM/VLM/VLA inference software for NVIDIA GPUs and hardware platforms. The role involves leading a team in specialized kernel development, runtime optimizations, and frameworks for LLM inference, with a strong emphasis on delivering production-grade, high-performance software.

NVIDIA is seeking a Senior Deep Learning Software Engineer to analyze and improve the performance of their deep learning inference ecosystem, specifically focusing on TensorRT. The role involves optimizing inference solutions for various NVIDIA accelerators, contributing to inference frameworks, and developing new model pipelines for generative AI and other applications.

NVIDIA is seeking a Senior Research Scientist to join their applied research team focused on building next-generation Conversational AI systems. The role involves developing new Deep Learning models for ASR, speech synthesis, NMT, and NLP, designing large-scale training algorithms, and open-sourcing models using NeMo. The position requires a PhD, significant research experience in speech recognition or NLP, strong Python and PyTorch skills, and a proven publication record.

NVIDIA is seeking a Senior Perception Engineer to design and productize its next-generation autonomous driving perception stack. The role focuses on the core 3D obstacle perception pipeline, involving architecture and algorithm design, and hands-on implementation using transformer-based, multi-modal, and vision-language techniques. Responsibilities include developing perception models, building production-grade deep learning models with pretraining and fine-tuning, defining KPI frameworks, contributing to data strategy, and collaborating with safety and systems teams. Requires a PhD/MS/BS with significant relevant experience, proficiency in PyTorch, Python/C++, and experience in data-driven development. Experience with autonomous driving/robotics perception, embedded platforms, optimization, and publications in leading conferences are desirable.

NVIDIA is seeking a Principal Deep Learning Senior Engineer to design, implement, and deploy end-to-end autonomous driving systems. The role focuses on leveraging LLMs, VLMs, and VLAs for advanced reasoning and planning in vehicles and robotics, involving model training, pre-training, fine-tuning, and integration into safety-critical systems.

Principal Deep Learning Engineer for NVIDIA's Autonomous Driving Perception team, focusing on developing, training, and deploying state-of-the-art perception systems (detection, segmentation, tracking) for vehicles. The role involves leading the end-to-end productization of these models, ensuring high quality and safety, defining data strategy, and providing technical leadership. Requires extensive experience in deep learning for computer vision and shipping commercial DL products.

Senior Deep Learning and Computer Vision Engineer for Autonomous Vehicles team, focusing on applying state-of-the-art techniques to build ground truth, train deep neural networks, and develop training pipelines and real-time inference run-times for self-driving cars.

NVIDIA is seeking a Senior Software Engineer to build and optimize AI inference systems for large-scale models, focusing on extreme efficiency and performance across multi-GPU, multi-node, and multi-cloud environments. The role involves architecting inference stacks, optimizing GPU kernels and compilers, driving benchmarks (MLPerf), and orchestrating large-scale deployments.

NVIDIA is seeking a Deep Learning Engineer with 8+ years of experience to build deep learning frameworks for LLM and VLM model compression. The role involves designing and implementing algorithms for pruning, NAS, and distillation, experimenting with model compression, and collaborating with researchers. Experience with PyTorch, LLM/VLM training or inference, and DL fundamentals are required. Experience with model compression techniques, building DL frameworks, and GPU programming are preferred. The role is based in Poland or Switzerland, with a salary range of 292,500 PLN - 650,000 PLN.

Machine Learning Engineer at NVIDIA focused on building GeForce G-Assist, an on-device AI assistant. The role involves evaluating and improving SLMs and VLMs, optimizing local inference (e.g., llama.cpp), designing RAG systems, and supporting agentic AI workflows. Requires strong C/C++ and Python skills, experience with local inference frameworks, and knowledge of SLM/VLM architectures and agentic AI patterns.

Principal Perception Engineer at NVIDIA for Autonomous Vehicles, focusing on designing and productizing next-generation 3D obstacle perception stacks using deep learning, transformers, and multi-modal techniques. The role involves technical leadership, hands-on algorithm development, production-grade model development, data strategy, and collaboration with safety and systems teams for large-scale deployment.

Senior Deep Learning Communication Architect role focused on optimizing communication performance for large-scale distributed deep learning training and inference. This involves identifying bottlenecks, designing efficient protocols, collaborating on hardware/software co-design, and exploring new communication technologies. The role requires deep understanding of parallelism techniques and experience with DNN frameworks and GPU computing.

NVIDIA is seeking a Senior Deep Learning Performance Architect to focus on hardware-software co-design for AI Inference performance. The role involves designing GPU and system architectures, analyzing deep learning algorithms, building performance models, and collaborating with various teams to guide AI direction.

Senior Systems Software Engineer focused on optimizing deep learning inference for autonomous vehicles and robotics on edge devices. Requires deep understanding of model architectures, kernel trace analysis, and evaluation of modern architectures on GPUs/SOCs, with a focus on TensorRT and compiler technology for embedded hardware.

This role focuses on optimizing and benchmarking Generative AI inference performance on NVIDIA's hardware accelerators, specifically working with frameworks like TensorRT-LLM, SGLang, and vLLM. The engineer will drive industry benchmark results by implementing optimizations in quantization, scheduling, memory management, and distributed inference. They will also define and optimize cutting-edge workloads, architect distributed inference systems from single-GPU to rack-scale, establish performance methodology using profiling, and contribute to open-source projects. The role requires strong programming skills (Python/C++), expertise in DL frameworks, and a deep understanding of LLM/VLM architectures and inference mechanics.

Senior Deep Learning Scientist role focused on developing, training, fine-tuning, and deploying streaming multimodal conversational AI systems. This includes speech, audio, vision, voice chat, and action, as well as human-AI interaction. The role involves applying research to define algorithmic improvements and scale them through the Nemotron platform, working on high-impact LLM products.

Senior/Principal Deep Learning Engineer focused on building evaluation methodologies and infrastructure for AI models (LLMs, RAG, agents, vision/multimodal), including contributing to an open-source platform and collaborating with the community. The role involves working with model training, inference, and product teams to provide evaluation signals for release and optimization decisions.

Senior Deep Learning Engineer at NVIDIA focused on optimizing inference for next-generation AI workloads including multi-agent systems and generative multimodal models. The role involves characterizing emerging workloads and developing novel optimization methods across the inference stack, from algorithmic to system level, on NVIDIA hardware. Collaboration with research, framework development, and silicon architecture teams is key.

Senior Deep Learning Architect focused on LLM inference performance optimization, benchmarking, and contributing to deep learning software projects like PyTorch, TRT-LLM, vLLM, and SGLang. Requires strong knowledge of deep learning inference serving, PyTorch, profiling, and GPU microarchitecture.

Lead Principal Engineer for Enterprise Agentic AI Platform at NVIDIA, focusing on building and scaling production-grade agentic AI systems, including multi-agent orchestration, memory systems, and evaluation pipelines. Requires deep expertise in distributed systems, Kubernetes, GPU inference, and hands-on coding in Python/Go.

Senior Systems Software Engineer focused on deep learning inference optimization for autonomous vehicles and robotics on edge hardware. The role involves analyzing and improving deep learning models on NVIDIA platforms, benchmarking performance, evaluating emerging model architectures, and collaborating with compiler, runtime, and hardware teams to deliver inference solutions.

Senior Deep Learning Compiler Engineer focused on optimizing inference and training performance for JAX and OpenXLA on NVIDIA GPUs. Develops compiler optimization algorithms, graph partitioning, tensor sharding, and code generation using MLIR, LLVM, and Triton.

Principal Software Engineer focused on advancing open-source LLM serving, specifically contributing to inference engines like vLLM and SGLang, optimizing them for NVIDIA GPUs and systems to achieve high-throughput, low-latency inference at scale. The role requires deep technical expertise in inference runtime architecture, GPU performance engineering, and distributed systems.

Senior Research Scientist at NVIDIA focusing on original research in generative AI, including image, video, 3D, and audio generation. The role involves implementing and training large-scale models, building research prototypes, and collaborating with product teams for technology transfer.

Senior Deep Learning Algorithm Engineer at NVIDIA to design, develop, and optimize core AI frameworks (Megatron Core, NeMo Framework) for LLM and Multimodal foundation model pretraining and post-training. The role involves implementing distributed training algorithms, model parallel paradigms, performance tuning, and expanding toolkits, working across the full model lifecycle from orchestration to deployment on NVIDIA GPU architectures.

Senior DL Algorithms Engineer focused on optimizing inference performance for language and multimodal models using NVIDIA's inference stack (NIMs, TRT-LLM). Role involves profiling, analysis, and collaboration across hardware/software layers to maximize performance on GPUs.

NVIDIA is seeking an experienced engineer to optimize LLM training workloads on high-performance computing systems, focusing on software stack optimization for thousands of GPUs and influencing future hardware roadmaps. The role involves performance analysis, profiling, and implementation across various layers of the deep learning platform, including building tools for automation and contributing to MLPerf benchmarks.

Research Scientist focused on AI accelerator hardware design, VLSI, and AI HW/SW co-design, applying machine learning and generative AI to hardware design flows and optimization techniques like quantization.

Develops GPU-accelerated deep learning software, including compilers, DSLs, and optimized kernels, for current and next-generation chips, focusing on performance analysis of AI workloads and integration with AI frameworks.

NVIDIA is seeking a Senior Research Scientist to conduct research at the intersection of AI, GPU computing, and Electronic Design Automation (EDA). The role involves defining and conducting original research in EDA algorithms, VLSI design methodology, and advanced machine learning techniques, with a focus on applying deep learning and GPU acceleration to improve chip design tools and flows. The scientist will collaborate with internal teams and the research community, publishing findings and potentially translating research into products.

Research Scientist focused on AI safety for multilingual, multimodal LLMs, including content safety, ML fairness, bias detection, and hallucination mitigation. The role involves developing datasets, moderator models, and training techniques (SFT, RL), and contributing to safety tools.

Research Scientist role focused on AI Accelerator Design and VLSI, involving AI HW/SW Co-Design, quantization, and applying generative AI to hardware design. Requires a PhD and experience in VLSI, computer architecture, or numerical algorithms for AI. Collaborates on research prototypes and publishes findings.

Research Scientist role at NVIDIA focusing on the intersection of AI and Quantum Computing. The role involves training AI models for quantum systems, advancing research in quantum simulation, and developing GPU-accelerated quantum tools. Requires a PhD, strong programming skills (Python, C++, PyTorch, JAX, CUDA), and a publication record in AI for quantum science or accelerated quantum simulations.

Research Scientist at NVIDIA focused on making deep learning models more efficient through techniques like quantization, sparsity, and optimized architectures. The role involves researching low-bit representations, pruning, and developing new algorithms for both training and inference, with a focus on understanding the root causes of efficiency gains and losses. The work directly influences next-generation hardware and state-of-the-art models, with opportunities for open-sourcing or publishing findings.

Senior Research Scientist at NVIDIA focused on Multi-Modal Language Models, driving Nemotron technology. The role involves improving model abilities, generalization, and efficiency through data synthesis, retraining, and developing training recipes for mixed modalities (text, image, video, audio). It also includes translating research into production, exploring evaluation paradigms, and contributing to open-source communities.

Senior engineer to optimize LLM/Omni model inference performance on NVIDIA's accelerated inference software stack, working across hardware and software layers. Involves enabling and optimizing open models, contributing code to frameworks like TRT-LLM and vLLM, profiling bottlenecks, and benchmarking.

Senior Software Engineer role focused on building multi-modal agentic AI solutions for NVIDIA's software stack, aiming to accelerate various stages of the SDLC. Responsibilities include leading design and development, and creating benchmarks.

NVIDIA is seeking a Developer Relations Manager to engage with research labs, acting as a technical advisor to accelerate the adoption of NVIDIA's AI platforms, with a deep focus on agentic AI systems. The role requires a PhD or equivalent experience, strong understanding of frontier research challenges in agents, and hands-on experience building or evaluating agent systems.

Research Scientist role focused on developing and training advanced generative AI models for graphics and gaming applications. The role involves research, pre-training, post-training, data pipeline development, and prototyping in real-time engines, with a focus on user experience improvements and bringing ideas to market.

Senior Software Engineer specializing in Deep Learning Inference to optimize GPU-accelerated software for AI applications. Focus on high-performance deep learning frameworks like SGLang and vLLM for efficient model serving and inference, improving performance across NVIDIA accelerators.

Senior Technical Lead for GenAI Product Integration at NVIDIA, focusing on integrating NVIDIA's GenAI software with enterprise ISV and CSP partners. The role involves defining technical strategy, building trusted relationships, and driving adoption of NVIDIA's offerings. Responsibilities include hands-on design and shipping of RAG, LLM inference, and Multi-Agent workflows, owning technical engagements, and representing partner needs to Product and Engineering teams. Requires strong background in AI/ML, Deep Learning, and building enterprise-grade GenAI systems, with experience in relevant programming languages and LLM application stages.

Senior Solutions Architect focused on Generative AI and Autonomous Vehicles, engaging with customers to guide adoption of NVIDIA's full-stack technologies, including AI platforms, CUDA-X libraries, and GenAI/Physical AI solutions. Responsibilities include technical mentorship, developing AV perception and planning models, simulations, synthetic data generation, AI-enhanced manipulation/navigation, and building collateral for AI workflows. Requires strong experience in AV systems, GenAI model development, Python/C++, Linux, DevOps, and DL/RL frameworks.

Senior Systems Software Engineer focused on building and shipping machine learning workflows and agentic systems, particularly leveraging LLMs/VLMs and computer vision for data generation and product features. The role involves converting research into production products, defining evaluation criteria, and iterating quickly.

NVIDIA is seeking engineers to develop algorithms and optimizations for their LPX inference and compiler stack, working at the intersection of large-scale systems, compilers, and deep learning to optimize neural network workloads on future NVIDIA platforms.

Senior Research Engineer at NVIDIA focused on building and improving AI coding agents, fine-tuning code LLMs, designing evaluations, and developing interfaces for AI agents to interact with NVIDIA's developer tools. The role involves shipping novel agents and features, contributing to benchmarks, and generating synthetic data for AI-for-code applications.

This role focuses on engaging with leading AI model builders to drive the adoption and optimize the performance of NVIDIA's hardware, systems, and software (e.g., GPUs, DGX, CUDA-X, NeMo, TensorRT) within their generative AI workflows, specifically for training and inference. The role involves technical integration, strengthening partnerships, influencing product roadmaps, and showcasing best practices for scalable AI model development pipelines.

This role focuses on building agentic infrastructure for test automation and quality engineering within the NVIDIA Omniverse platform. The engineer will design and deploy multi-agent systems, orchestration frameworks, and autonomous pipelines, with a strong emphasis on evaluating agent output quality and establishing observability for these workflows. The goal is to enable engineers to ship high-quality software with greater speed and confidence.

This role leads the research agenda and architectural direction for NVIDIA's AI networking systems, focusing on high-performance communication at scale. It involves original research, hardware-software co-optimization, and integrating networking into AI serving stacks, with a requirement to publish findings and ship production-grade software.

NVIDIA is seeking a Senior Software Engineer to build and scale RL post-training infrastructure, focusing on distributed systems, high-performance computing, and deep learning infrastructure. The role involves architecting and optimizing RL training-inference-rollout loops, ensuring fault tolerance and elastic scaling, and collaborating with researchers and hardware teams.

Senior Applied AI Researcher at NVIDIA Israel focusing on deep learning for biology. The role involves developing foundational, generative, and agentic AI models, including LLMs and multimodal systems, for biological data and digital twin applications in healthcare. Responsibilities include research, implementation, evaluation, and collaboration in an interdisciplinary team.

Senior Research Engineer at NVIDIA to design and build video search technologies for Autonomous Vehicles, Robotics, and Medical applications, focusing on exabyte scale and agentic search. The role involves developing and integrating innovative video search approaches, benchmarking retrieval methods, and collaborating with researchers and product teams to build robust physical AI dataset search workflows.

Senior AI Software Engineer focused on developing kernel libraries and inference systems software to accelerate AI workloads, including LLMs and agents, on NVIDIA's hardware. Responsibilities include innovating and optimizing kernels, designing abstractions for serving engines, and building compilers/runtimes.

Develops libraries, code generators, and GPU kernel technologies for NVIDIA's AI inference systems software stack, focusing on accelerating AI inference through efficient kernels, abstractions, and runtimes for LLMs and agents.

NVIDIA is hiring a Senior AI Compiler Engineer to build an MLIR-based AI compiler for their inference engine, focusing on performance, low memory usage, and usability across data center and edge. The role involves developing graph representations, optimizations, defining APIs, and implementing compiler optimizations and kernel generation for neural networks.

Senior DL Software Engineer focused on optimizing and deploying large multimodal models (LLMs/VLMs) for real-time robotic execution in autonomous vehicles. The role involves advanced model compression, quantization, pruning, distillation, and inference optimization techniques for edge deployment on NVIDIA hardware, integrating with C++ production environments.

NVIDIA is seeking a Solutions Architect to help enterprise customers adopt NVIDIA AI software and models. This role involves developing end-to-end AI solutions, tackling complex challenges across the AI model lifecycle (data processing, orchestration, training, post-training, RL, evaluation, optimization), and supporting a broad model portfolio. The architect will partner with customers to understand their needs and deliver customized AI solutions, contributing to product improvement and sharing knowledge through open-source projects, product engineering, or training.

Senior Solutions Architect for Retail at NVIDIA, focusing on developing and deploying Agentic AI solutions for enterprise clients. The role involves building complex agentic systems, RAG pipelines, and optimizing inference performance using NVIDIA's AI infrastructure. Requires strong programming skills, experience with LLM applications, and agentic frameworks.

NVIDIA is seeking a Senior ML Evaluation Engineer for their Autonomous Vehicles team. The role involves designing and building learned evaluation pipelines using LLMs, VLMs, and agentic workflows to assess driving behavior. The engineer will define evaluation methodologies, build golden-set frameworks, and contribute to the transition from rule-based to learned evaluation systems. This position requires a strong background in ML system development, software engineering, and experience with large-scale data processing, with a focus on shipping production ML systems.

NVIDIA is seeking a Senior Solutions Architect for Autonomous Vehicles and Robotics to help customers accelerate Physical AI workloads using NVIDIA's full-stack technologies. The role involves engaging with customers to optimize training, simulations, and synthetic data generation for AV perception and planning models, providing technical expertise, and driving full-stack adoption. The candidate will analyze and optimize AI models for GPU performance, build collateral for various AI workflows, and provide technical leadership. Requires 8+ years of ML/DL Infra experience in AVs, proficiency in Python, CUDA/C++, Linux, DevOps tools, and a strong understanding of AV models and simulations. Experience with model deployment at scale and robotics model development is a plus. The role focuses on the data and infrastructure aspects of AI model development and deployment in the AV domain.

Solutions Architect focused on building and deploying agentic AI applications and enterprise agents, with a strong emphasis on localization, performance optimization, and leveraging NVIDIA's AI infrastructure.

Principal Engineer to lead the deployment of advanced AI agent frameworks and local runtimes on Windows and NVIDIA GPUs, focusing on open-source agents, local inference, privacy, and security for consumer PCs.

This role focuses on building production-grade AI applications and agent systems for enterprises, involving design, orchestration, integration, observability, and deployment on NVIDIA's platforms. The candidate will lead by example as a hands-on developer, creating proof-of-concept solutions and deployable single-agent and multi-agent systems to solve real business problems.

Senior Robotics Research Engineer focused on building physical AI for drug discovery labs, involving robotics simulation, perception, task and motion planning, and training robots for manipulation tasks using imitation and reinforcement learning.

Research and analysis engineer focused on optimizing AI networking performance for large-scale LLM training on distributed GPU clusters, involving profiling, analysis, tool development, and collaboration across hardware and software teams.

NVIDIA is seeking a Senior HPC and AI Network Software Architect to design and build scalable AI infrastructure for distributed training and inference. The role involves developing software and hardware approaches to optimize communication efficiency and performance across large-scale systems, collaborating with AI framework teams and hardware teams.

Senior Engineering Manager to define and drive NVIDIA's JAX strategy, coordinating multiple teams to ensure JAX delivers peak performance across heterogeneous hardware (GPUs, CPUs, LPUs). The role involves supporting emerging needs across training, post-training, inference, and robotics, bridging new hardware capabilities with AI trends. Key responsibilities include driving engineering contribution strategy, promoting teamwork, building partnerships with open-source projects, designing processes, and leading a high-performing engineering organization.

NVIDIA is seeking a Senior DGX Cloud AI Infrastructure Software Engineer to develop and optimize infrastructure software and tools for large-scale AI training, post-training, and inference. The role focuses on improving efficiency and resiliency of AI workloads, co-designing APIs, and enhancing AI platforms, requiring strong debugging and distributed systems experience.

Principal Engineer for Autonomous Vehicles and Physical AI Solutions at NVIDIA, focusing on strategic automotive and robotics partnerships in Japan. The role involves tailoring NVIDIA's full-stack AI technologies (DRIVE AGX Thor, Alpamayo, Cosmos) to meet production-grade requirements of OEMs, bridging AI, system optimization, and safety architecture. Responsibilities include innovating with reasoning VLA models, ensuring engineering alignment for partnerships, representing NVIDIA in industry forums, serving as technical authority for RFIs/RFQs, and establishing standards for physical AI production deployment.

This role focuses on building and optimizing GPU communication kernels for large-scale AI systems, linking GPU computing with networking. The Senior GPU Networking Architect will leverage deep knowledge of GPU architecture to improve kernel efficiency, minimize latency, and overlap computation with communication. Responsibilities include developing GPU-resident communication primitives, profiling and tuning kernels, and collaborating with various teams to co-design communication strategies. The role requires strong CUDA programming, GPU architecture fundamentals, and systems-level C/C++ development.

NVIDIA is seeking a Solutions Architect to assist researchers and developers in accelerating their AI workloads using NVIDIA's platform. The role involves creating technical engagements, proposing state-of-the-art training and optimization frameworks, and promoting collaborative results. Requires 5+ years of experience in the full AI model lifecycle, including pre-training, fine-tuning, post-training, optimization, and evaluation, along with strong software engineering skills.

NVIDIA is seeking an engineer to develop and productionize reinforcement learning (RL) capabilities for agent teams within an enterprise context. The role involves evaluating and adapting RL approaches, designing reward environments, operationalizing training backends, and integrating with existing ML services. Responsibilities include leading data curation, designing RL training loops, integrating with GPU infrastructure, building observability, and collaborating with various platform and customer teams. The ideal candidate has extensive experience in operationalizing fine-tuning and RL techniques, familiarity with distributed training frameworks and MLOps, and proficiency in relevant programming languages.

NVIDIA is seeking a Director of Engineering to lead the design and deployment of end-to-end autonomous driving systems. This role focuses on leveraging LLMs, VLMs, and VLAs for advanced planning and reasoning in vehicles and robotics, involving strategic leadership, team management, and technical oversight of ML model development and integration into safety-critical production environments.

Senior AI/ML Solution Engineer focused on designing and building AI-powered development pipelines, evaluating ML approaches for code generation and review, and driving adoption of AI-assisted software development. The role involves architecting feedback and evaluation systems, leading proof-of-concept development, and collaborating on risk-based development levels.

Robotics Research Intern at NVIDIA focusing on fundamental and applied research across the full robotics stack, including perception, planning, control, reinforcement learning, imitation learning, and simulation. The goal is to transform research paradigms, transfer into products, and create new markets.

Senior Engineering Manager to lead the strategy and execution for NVIDIA’s agentic developer platform, focusing on building, evaluating, and improving autonomous agents. The role involves identifying gaps, driving POCs, operationalizing approaches into reusable components, and establishing governance and safety mechanisms to scale autonomous systems within NVIDIA.

Director of Perception for Autonomous Vehicles at NVIDIA, leading teams to develop and deploy state-of-the-art deep learning models for real-time 3D world reconstruction and navigation. This role involves end-to-end ownership of the ML lifecycle, from data generation to deployment on NVIDIA DRIVE platforms, with a strong emphasis on safety-critical systems and cross-functional collaboration.

NVIDIA is seeking a PhD Research Intern to apply modern AI methods to climate and weather simulation. The role involves proposing, researching, and prototyping innovative ideas, publishing groundbreaking work, and contributing to technology transfer. The intern will utilize NVIDIA GPUs for cutting-edge research at the intersection of AI and climate science.

Senior Software Engineer to build and deploy production AI for autonomous vehicles, focusing on training, fine-tuning, and optimizing deep learning models for real-time inference on NVIDIA GPUs. Requires strong C++/Python, deep learning training experience, and Linux development skills, with a preference for GPU programming, computer vision, or robotics.

NVIDIA is looking for a Senior Software Architect to design and optimize inference infrastructure for large language models running on GPU clusters. The role involves working across software and hardware domains to define deployment and scaling strategies, optimize latency and throughput, and collaborate with various teams to ensure high-performance solutions.

Senior engineer focused on optimizing AI training workloads for performance on NVIDIA's hardware and software stack, from drivers to DL frameworks, impacting hardware/software roadmap and contributing to MLPerf benchmarks.

Senior Research Engineer focused on neural reconstruction, developing and integrating neural rendering approaches for generative video, segmentation, and 3D reconstruction. The role involves adapting and fine-tuning generative models, collaborating on ML workflows, and contributing to core NVIDIA products. Requires strong Python and ML library skills, with experience in training and optimizing models.

NVIDIA is seeking a Senior Capability Development Engineer to develop and enhance internal RAG and Agent platforms for Ops Engineering productivity. The role involves developing, training, fine-tuning, and deploying multimodal LLMs, building LLM-based applications (RAG, TEXT2SQL, Agents), applying advanced tuning techniques, measuring performance, analyzing accuracy/bias, and driving dataset development. Requires strong Python skills, familiarity with ML/DL frameworks and LLMs, and practical experience with LLM training frameworks.

Senior AI Security Researcher at NVIDIA focusing on testing, attacking, defending, and safely deploying frontier AI systems, agentic applications, and AI-enabled security automation. The role involves developing new methods, tools, and evaluations to understand and mitigate security risks across various AI components.

Senior Software Engineer focused on integrating NVIDIA's NIM microservices and Blueprints into agentic AI frameworks. The role involves building and maintaining agentic workflows, developing test harnesses, and contributing to the open-source agentic AI ecosystem.

NVIDIA is seeking engineers to develop algorithms and optimizations for their LPX inference and compiler stack, working at the intersection of large-scale systems, compilers, and deep learning to optimize neural network workloads on future NVIDIA platforms. The role involves building and maintaining high-performance runtime and compiler components, defining workload mappings, integrating with the SW ecosystem, benchmarking, profiling, and collaborating with hardware teams. It also includes prototyping new compilation techniques and publishing technical work.

Senior Deep Learning Framework Communications Engineer at NVIDIA, focusing on integrating and optimizing communication libraries (NCCL, NVSHMEM) within AI frameworks (PyTorch, TRT-LLM, vLLM, JAX) to enhance performance for large-scale AI training and inference. The role involves deep analysis of AI workloads, compiler improvements, and kernel authoring for multi-GPU systems.

Develops and enhances machine learning frameworks (NVIDIA PhysicsNeMo, NVIDIA Earth2Studio) for scientific ML technology in weather, climate, and earth system modeling. Focuses on implementing new deep learning techniques and enhancing Earth-2 technologies.

Senior Solutions Architect role focused on assisting customers in deploying Generative AI solutions, particularly for data processing and agentic workflows, using NVIDIA's AI technology stack. The role involves technical advisory, system design, and implementation at scale, with a strong emphasis on Deep Learning, LLMs, and GPU technologies.

Senior Software Architect role at NVIDIA focused on designing and implementing next-generation data center platforms and scalable communication software for AI and HPC workloads. The role involves investigating performance bottlenecks, developing new communication technologies, exploring hardware/software co-design, and building proofs-of-concept to drive innovation in large-scale GPU clusters.

Senior Solutions Architect focused on Deep Learning and Agentic AI tools, collaborating with customers to build solutions using NVIDIA technology. Responsibilities include technical sales support, integrating NVIDIA tech into HPC, championing Deep Learning internally, and developing demo solutions.

Senior Software Engineer focused on optimizing deep learning inference for LLMs and omnimodal architectures on NVIDIA hardware, including GPU kernel tuning, distributed inference, and contributing to open-source libraries.

Senior Hardware Architect role focused on designing next-generation GPUs and systems to advance the state of AI, analyzing deep learning workloads, and proposing new features for acceleration. Requires 8+ years of experience in performance, hardware architecture, and deep learning analysis.

NVIDIA is seeking an Applied Machine Learning Engineer for their Circuit Design team, focusing on building AI-driven software systems that combine automation algorithms, DL models, and agentic workflows to accelerate end-to-end circuit design. The role involves working with hardware design data, circuit optimization, and developing AI/ML solutions for EDA, with a focus on agent-driven design exploration and optimization.

Senior Solutions Architect role focused on customer engagements for NVIDIA's generative AI technologies, involving AI model training and deployment optimization, particularly for LLMs and recommenders in the consumer internet industry. Requires strong coding, GPU optimization, and communication skills.

NVIDIA is seeking an AI Compiler Engineer to optimize kernel generation and computational graph optimizations for AI inference and training workloads on next-generation GPUs. The role involves hands-on development, collaboration on hardware/software co-design, and scaling AI deployments in datacenters.

The role focuses on optimizing LLM inference server performance, workload characterization, and benchmarking for NVIDIA's GPUs. It involves collaborating with AI startups, developing performance tools, contributing to deep learning software projects, and guiding inference serving direction.

NVIDIA is seeking a Senior Deep Learning Scientist to work on their Speech AI product, Riva. The role involves training speech synthesis models (mel-spectrogram and vocoder), measuring and analyzing model performance, maintaining the TTS evaluation system, and improving speech data processing and training set preparation. The ideal candidate has a Master's or PhD, 5+ years of ML/AI experience, strong Python and PyTorch skills, and hands-on experience training speech synthesis models.

NVIDIA is seeking a Senior Performance Engineer to optimize LLM inference infrastructure on GPUs, focusing on throughput, memory efficiency, and scalability. The role involves designing and implementing high-performance pipelines, profiling, tuning model execution, and innovating techniques like Speculative Decoding and quantization. Experience with deep learning frameworks and performance debugging is required.

NVIDIA is seeking an Applied AI Engineer to explore and architect generative AI solutions, including LLMs, RAGs, and Agentic AI workflows, for Design-for-Test (DFT) and VLSI problems. The role involves deploying predictive ML models for silicon lifecycle management and collaborating with VLSI/DFX teams to integrate AI solutions. Experience in applied ML for chip design and deploying generative AI for engineering use cases is required.

Senior Staff Software Engineer to own engineering efforts for NVIDIA enterprise systems, transforming support into AI-infused automated resolution systems using LLM-based agents, tool calling, RAG, and orchestration frameworks. Requires full-stack experience, strong systems thinking, and incident management skills.

NVIDIA is seeking software engineers to develop and optimize inferencing software for AI models, specifically focusing on TensorRT-LLM. This role involves performance analysis, tuning, and collaboration across teams to advance machine learning inferencing capabilities.

This role focuses on building and deploying AI inference solutions at scale using NVIDIA's GPU technology and Kubernetes. The Solutions Architect will collaborate with engineering, DevOps, and customers to optimize and serve generative AI models, ensuring low-latency inference in enterprise environments.

NVIDIA is seeking Solutions Architects to build and deploy agentic AI applications at scale for enterprises, focusing on integrating enterprise data, developing multi-modal dialogue systems, and task-specific agents. The role involves working with agentic frameworks, providing feedback to improve software products, and educating vertical teams.

Senior Solutions Architect role focused on customer engagements, improving AI workload performance, and developing proof-of-concepts for Generative AI solutions (LLMs, recommenders) using NVIDIA software and technologies. Requires strong coding, GPU optimization, and communication skills.

NVIDIA is seeking a Principal Deep Learning Communication Architect to lead the technical roadmap for communication libraries across next-generation platforms, ensuring seamless scaling of models to massive clusters. The role involves designing and optimizing communication primitives for heterogeneous interconnects, co-designing with application developers and silicon architects, and developing analytical models for system behavior. Expertise in parallel computing, HPC/distributed deep learning, inference engines, and GPU architecture is required.

This role is a Technical Lead focused on Generative AI within Autonomous Vehicles, engaging with developer ecosystems and partners to promote NVIDIA's AI platforms. The candidate will act as a technical advisor, develop expertise in NVIDIA's platforms, create enablement resources, and represent partner needs internally. Requires a strong technical background in AI, AV systems, and GenAI model development, with experience in production code, DevOps, and DL/RL frameworks.

Senior Software Engineer at NVIDIA for Autonomous Vehicles, focusing on Computer Vision and Machine Learning for offline perception tasks. Responsibilities include advancing DL components for training and inference, developing tools for large datasets, and integrating DL algorithms into large-scale pipelines.

NVIDIA is seeking a Senior AI Software Development Engineer for its TensorRT-LLM team. The role involves crafting and developing robust, scalable inference software for LLMs, focusing on performance analysis, optimization, and tuning. The engineer will write high-quality C++/Python code for the core backend software and collaborate with various teams to guide deep learning inference direction. A strong background in software development, LLM inference techniques, and deep learning frameworks is required.

Product Manager for NVIDIA Dynamo, a distributed inference framework for LLMs and Generative AI. Focuses on defining the roadmap for high-scale serving, optimizing hardware-software co-design, and developing agentic inference capabilities. Collaborates with engineering, open-source communities, and customers to integrate model evaluation into workflows.

Senior Software Engineer role focused on building and deploying production-grade RAG solutions and AI agents. The role involves designing and implementing scalable RAG architectures, developing AI agents with reasoning and multi-step execution capabilities, and orchestrating complex microservices deployments. Emphasis on optimizing RAG pipelines for accuracy, relevance, and performance, and driving continuous improvement through rigorous evaluation and collaboration.

Senior Systems Software Engineer to architect and deploy production-grade AI agents for NVIDIA's e-commerce platform, focusing on personalization, logistics, and customer experience. Requires expertise in Python, Java, GoLang, distributed systems, and AI frameworks like LangChain/LangGraph.

Senior Applied ML Scientist at NVIDIA to develop ML and data-science solutions for predictive-maintenance, root-cause analysis, and AIOPS, driving projects from ideation to production within the Applied Networking AI group.

NVIDIA is seeking an AI-focused Solutions Architect with expertise in LLMs, generative AI, agentic AI, or recommender systems. The role involves providing technical expertise to customers, assisting with GPU infrastructure for AI, optimizing training and inference pipelines, and gathering customer feedback for product development. This position requires 3+ years of experience in AI for large models and proficiency with AI tools.

Senior Deep Learning Solution Architect at NVIDIA, focusing on LLM inference and training acceleration, performance optimization, and contributing to open-source frameworks like SGLang and vLLM. The role involves developing and optimizing inference frameworks, KV cache offloading, and exploring distributed training performance.

This role focuses on architecting physical AI platforms for automotive and robotics, specifically defining the SoC architecture for embedded computer vision and AI systems. The individual will analyze use cases, map requirements to hardware/software features, define system requirements, and drive recommendations into product roadmaps. The role involves deep benchmarking, customer interaction, technical leadership, and mentorship, with a strong emphasis on functional safety (ISO 26262, SOTIF).

Senior Technical Program Manager to drive and coordinate cross-functional teams for large-scale technical projects in agentic AI, connecting foundation models with real-world applications for edge deployment and AI workflows.

NVIDIA is looking for an AI Acceleration & Optimization Engineer to optimize the performance, scalability, and efficiency of AI models (LLMs, VLMs, diffusion, multimodal) on NVIDIA GPU platforms. The role involves profiling, identifying bottlenecks, and applying optimization techniques like quantization and kernel fusion, using tools such as CUDA, TensorRT, and Nsight. Collaboration with various teams (algorithms, systems, hardware, research, CUDA, compiler, frameworks) is key to bringing models from research to production.

Principal Software Engineer to lead security foundations for autonomous, self-evolving agents in an enterprise setting. This role involves defining security requirements, designing scalable architectures with guardrails, implementing isolation and access controls, building secure data access pathways, establishing observability and auditing, and operating a continuous evaluation framework for agent behavior. The goal is to enable developer velocity while ensuring robust safety and security for agents that generate and execute code and access data.

NVIDIA is seeking a Senior Machine Learning Applications and Compiler Engineer to develop algorithms and optimizations for their LPX inference and compiler stack, working at the intersection of large-scale systems, compilers, and deep learning to map neural network workloads onto future NVIDIA platforms.

Senior Engineer to apply AI/ML and LLMs to power analysis and optimization for NVIDIA's GPUs and SoCs. Focus on developing and productionizing ML/RL models and custom LLMs to improve energy efficiency, interpret power data, and recommend optimizations. Involves RTL analysis, Verilog prototyping, and automation.

Senior Software Engineer to develop production automotive software for AI inference and agent orchestration in C++ for embedded platforms. Focus on building next-generation automotive software applications, including in-car agentic AI and inference of LLM/VLM/VLA models on NVIDIA GPUs.

Develops algorithms and optimizations for NVIDIA's LPX inference and compiler stack, focusing on mapping neural network workloads onto future NVIDIA platforms and optimizing end-to-end inference performance. Requires strong software engineering, compiler/runtime development, and deep learning framework experience.

NVIDIA is seeking a DL System Software Engineer to develop an AI Platform for efficient inference and training of large-scale models on GPU clusters. The role involves designing and building solutions for scheduling workloads, resource management, and performance optimization, working with various NVIDIA AI technologies.

NVIDIA is seeking a Senior Software Engineer for its TensorRT-LLM team to develop and scale inferencing software for LLMs and Generative AI. The role involves crafting robust inferencing software, performing benchmarking and profiling for GPU applications, writing high-quality Python code for LLM inference, and improving the TensorRT-LLM library. Collaboration with software, research, and product teams is key.

Senior Software Engineer to develop and optimize a state-of-the-art inference framework for Large Language, Vision-Language, and Multimodal models on edge and embedded platforms, focusing on real-time performance and constrained environments.

Senior Performance Engineer at NVIDIA focused on optimizing Deep Learning models and frameworks (PyTorch, JAX) for NVIDIA GPUs. The role involves building and supporting Transformer Engine, collaborating on systems research for performance improvements, implementing and benchmarking new DL models, contributing to MLPerf, and engaging with the open-source community and enterprise customers. It also involves influencing future hardware and software design.

Senior System Software Engineer focused on 3D Computer Vision at NVIDIA, involving the development and deployment of advanced neural reconstruction models for generating 3D scenes. The role requires strong programming skills in Python and C/C++, a background in computer vision and deep learning, and experience with production-grade software development.

Senior AI Research Scientist role focused on developing digital twins for chemical, biological, and physical laboratories, integrating AI agents with science experiments, and collaborating with robotics and software engineers. Requires a Ph.D. and 5+ years of AI research experience in robotics.

Senior Software Engineer focused on optimizing quantized inference for LLMs by implementing recipes, developing kernels, and collaborating on inference engines like vLLM and TRT-LLM. The role involves model export pipelines, benchmarking, and data analysis tooling.

NVIDIA is seeking a Senior Compiler Engineer to optimize AI inference performance for their Deep Learning & AI Compiler (DLC) team. The role involves analyzing deep learning networks, developing compiler optimization algorithms, and collaborating with framework and architecture teams to accelerate next-generation deep learning software for various AI applications.

NVIDIA is seeking a Senior Compiler Engineer to join its Deep Learning & AI Compiler (DLC) team. The role involves analyzing deep learning networks, developing compiler optimization algorithms, and collaborating with framework and architecture teams to accelerate AI inference performance on NVIDIA GPUs. The compiler is critical for data centers, personal devices, automotive, and robotics, focusing on inference performance, build time, memory footprints, and ease of use.

Research Scientist focused on security and privacy for AI systems, aiming to develop hardware, software, and algorithms for trustworthy AI with verifiable protection. Requires a PhD and expertise in areas like computer architecture, programming languages, applied cryptography, or AI/ML algorithms, with a strong publication record.

This role focuses on driving the technical integration of NVIDIA's Generative AI software with enterprise partners, including ISVs and CSPs. The Principal GenAI Engagement Lead will build trusted relationships, accelerate adoption, and influence product direction by designing and shipping methodologies, code, and reference architectures for RAG, LLM inference, and Multi-Agent workflows. The role requires a strong background in AI/ML, deep learning, and enterprise-grade GenAI systems, with experience in various LLM application stages and MLOps. The individual will act as the key technical lead, ensuring the deployment of robust, scalable GenAI solutions.

Senior Deep Learning Performance Architect at NVIDIA to design and evaluate hardware architectures for AI/HPC applications, focusing on LLM inference and training performance, and optimizing system bottlenecks.

NVIDIA seeks a Solutions Architect for their EMEA team to drive AI adoption in drug discovery within the biopharma industry. The role involves acting as a technical advisor to pharmaceutical companies, biotechs, and research organizations, leveraging NVIDIA's computing platform. Responsibilities include building proof-of-concept demonstrations, scaling AI deployments, and supporting business development by guiding customers on production-grade inference, model training, RL, and post-training algorithms. The role also involves exploring foundation models, agentic LLM applications, and physical AI in biopharma, providing feedback to internal teams, and documenting/teaching NVIDIA solutions.

Seeking a Senior GPU System Architect to design multi-GPU scale-up and scale-out systems for AI and HPC datacenters. The role involves defining system architectures that integrate GPU compute, memory, and interconnects for optimal AI performance and scalability. Requires deep experience in system-level fabric/networking architecture and hardware-software co-design.

Senior Software System Engineer to customize and expand NVIDIA’s autonomous driving solutions, delivering and scaling a foundation model-based end-to-end stack for autonomous driving. Involves applied research and development of deep learning models, issue triage, performance maintenance, and collaboration to build a unified production system.

NVIDIA is seeking a Solution Architect to promote adoption and provide technical support for their GPU-accelerated computing solutions, focusing on generative AI, machine learning, and deep learning for enterprise clients in Japan. The role involves pre-sales activities, technical support for model training and deployment, and developing solutions for inference and agent-based systems.

NVIDIA is seeking an Applied AI Engineer to design, develop, and integrate AI/LLM-powered systems into their chip design and automation infrastructure. The role involves architecting and implementing solutions to enhance workflow efficiency, scalability, and intelligence, driving initiatives from concept to deployment. Requires hands-on experience building and deploying ML/AI systems or data-intensive backend services, with a focus on owning AI agents or LLM-powered workflows end-to-end.

Senior/Principal Engineer in robotics systems, focusing on foundation models and full-stack technology for humanoid robots. Responsibilities include designing teleoperation software, optimizing control stacks, deploying neural network models on hardware, and collaborating on the MLOps lifecycle. Requires strong robotics and software engineering background, with experience in real-time control and deploying ML models on robotic hardware.

Senior Perception Engineer at NVIDIA focused on developing and productizing autonomous driving solutions using deep learning and multi-sensor fusion. The role involves applied research, algorithm development, and ensuring solutions meet production requirements for safety, latency, and robustness.

Senior Software Engineer to develop core libraries for Agentic Applications, focusing on building foundational technology, scalable capabilities, reusable blocks, and high-quality libraries to accelerate developer productivity and ensure agent quality. The role involves benchmarking, identifying bottlenecks, and optimizing performance, cost, and latency for agents. Collaboration with teams on data pipelines, RAG, vector databases, and GPU-optimized workflows is expected.

NVIDIA is seeking a Software Engineering Intern to join its AI Tools and Infrastructure team, focusing on Agentic AI. The intern will work with LLMs and orchestration frameworks to design, build, and deploy intelligent agents and AI tools, gaining exposure to the full lifecycle of agent development from conceptualization to deployment.

NVIDIA is seeking a Solutions Architect with expertise in AI for Chemistry and Materials Science to lead research and application efforts. The role involves driving collaborations, mentoring junior members, developing technical materials, and staying updated on AI advancements in the field. Requires a PhD or equivalent experience and proficiency in Python and AI/ML libraries like PyTorch.

NVIDIA is seeking an Applied AI Engineer to explore and architect generative AI solutions, including LLMs, RAGs, and Agentic AI workflows, for Design-for-Test (DFT) and VLSI problems. The role involves deploying predictive ML models for silicon lifecycle management and collaborating with VLSI/DFX teams to integrate AI solutions. Experience in applied ML for chip design and deploying generative AI for engineering use cases is required.

Senior Data Center Performance Engineer at NVIDIA focused on benchmarking and optimizing data center platforms for AI training, inference, and HPC workloads. Responsibilities include designing benchmarks, characterizing workloads, identifying bottlenecks, and driving performance improvements through system tuning and architectural recommendations.

This role focuses on driving the technical integration of Generative AI software with enterprise partners, involving hands-on design and deployment of RAG, LLM inference, and Multi-Agent workflows. The position requires deep technical expertise in AI/ML, partner engagement, and understanding of the GenAI lifecycle, with a focus on production deployments and influencing product roadmaps.

This role focuses on engineering and deploying AI infrastructure and solutions for strategic customers, optimizing large-scale training and inference workloads on NVIDIA's AI platform. It involves MLOps, Kubernetes, GPU scheduling, and performance tuning, with a strong emphasis on customer-facing technical support and collaboration.

Research Engineer focused on analyzing and optimizing the performance of large-scale distributed LLM training and inference on GPU clusters, with a strong emphasis on networking aspects.

NVIDIA is seeking an AI Solutions Architect with deep expertise in AI solutions and scalable data center infrastructure. The role involves embedding NVIDIA software into customer architectures, improving application performance, and establishing technical foundations for next-generation AI systems. Responsibilities include supporting business development, working directly with developers and customers, analyzing architectures for acceleration opportunities, and delivering trainings.

NVIDIA is seeking a Director of System Software Engineering to lead teams responsible for the full lifecycle of Vision AI strategy, from model onboarding to production deployment. The role focuses on transforming foundation models into real-time, GPU-accelerated video intelligence systems, scaling multimodal reasoning, and enabling agentic development workflows. Key responsibilities include architecting and operationalizing inference acceleration, driving implementations of frameworks like TensorRT and VLLM, collaborating with partners on custom models, and ensuring performance benchmarking. The ideal candidate has extensive experience in deep learning, GPU optimization, and leading engineering teams in embedded and enterprise platforms.

Director of Engineering for NVIDIA's Isaac for Healthcare initiative, focusing on building a platform for healthcare robotics companies to develop, simulate, train, and deploy physical AI systems. The role involves platform leadership, team building, partner enablement, technical strategy, and cross-functional collaboration, with a strong emphasis on shipping sophisticated software platforms at scale.

Manager of Solutions Architecture for NVIDIA's Global Partner Team, focusing on leading technical engagements with GSIs and AI consulting firms. The role involves building and scaling Agentic AI services, providing architectural oversight for complex AI workflows, and collaborating with product and engineering teams. Requires deep technical expertise in Generative/Agentic AI, RAG, LLM orchestration, and AI infrastructure.

NVIDIA is seeking an AI Engineer to build and operate AI application-layer services for SOC design automation, including assistants, retrieval, Q&A, workflow automation, and AI agents. The role involves designing LLM-backed services, building RAG and knowledge systems, applying agent and orchestration patterns, improving developer experience with AI-assisted coding, and owning reliability and evaluation. Requires strong Python, experience shipping services, and hands-on use of LLM frameworks and RAG.

NVIDIA is seeking a Director to define and build the Retail & CPG Industries product platform. This role involves architecting and developing a platform leveraging NVIDIA's full stack, including Agentic AI and accelerated computing, to reshape digital commerce, supply chains, and intelligent stores. The platform will utilize NVIDIA Nemo microservices and Nemotron models, with a focus on Agentic AI for various business functions. The ideal candidate will have hands-on development experience with AI agents, LLMs, RAG, and distributed systems, and will collaborate with engineering teams to deliver a production-ready, scalable platform.

Solutions Architect role focused on leading AI research and application, mentoring technical members, and fostering AI ecosystem development using NVIDIA technologies. Requires expertise in AI research areas like Digital Twins, Synthetic Data Generation, Immersive Multimedia, and Generative AI, with a strong background in AI model training and Python/PyTorch.

This role focuses on enhancing the efficiency of AI and ML research on GPU clusters by collaborating with researchers to identify and address infrastructure deficiencies. The engineer will optimize performance, monitor resource utilization, and contribute to the AI/ML infrastructure ecosystem, keeping up-to-date with the latest AI/ML technologies.

NVIDIA DGX Cloud Team is seeking a Principal Cloud Services Software Engineer to develop and optimize AI infrastructure services for large-scale AI training workflows. The role involves designing and implementing resilient, efficient services orchestrated by Kubernetes, with a focus on backend development, distributed systems, and high-performance computing.

Senior Solutions Architect focused on deploying and validating AI factories, specifically running and debugging AI/LLM workloads on GPU clusters. Responsibilities include setting up environments, executing benchmarks, resolving performance issues, building observability, and recommending optimizations.

Senior Software Engineer to design, build, and optimize containerized inference execution for 3D Vision Language Models (VLMs) for neural reconstruction, turning research into production-grade software (NIMs). The role involves developing benchmarks, releasing and maintaining models, contributing to open-source projects like vLLM, and collaborating with research and product teams. Requires experience with AI distributed systems, inference platforms, Python/C++, and software engineering fundamentals.

NVIDIA is seeking an AI Computing Software Development Engineer for its TensorRT team to craft and develop robust inferencing software for GPUs, focusing on performance analysis, optimization, and tuning. The role involves collaborating with various teams to guide machine learning inferencing direction and potentially publishing key results.

Senior Software Engineer to develop and optimize high-performance Vision AI pipelines and large-scale distributed services for processing video, image, and 3D data. The role involves crafting real-time systems, developing multi-modal perception, using simulation/synthetic data, and profiling/tuning GPU-accelerated inference pipelines. Collaboration with research and platform teams is key, with an emphasis on bringing research into production at scale.

Senior Software Engineer role focused on building and productizing ML tools for optimizing AI workloads (LLM training/inference) across GPU/CPU clusters, with a focus on networking and system resource utilization. Involves distributed deep learning, ML-based optimization techniques, and performance analysis.

NVIDIA is seeking a Machine Learning Intern to assist with AI technology development and demonstrations. The intern will work with NVIDIA SDKs, engage with the AI community, and contribute to machine learning projects and AI software development.

Senior engineer to build the main stack for autonomous driving, focusing on prediction, decision-making, planning, and control architecture. This includes crafting system-level safety, implementing end-to-end data-driven AV pipelines, large-scale model inference, and integrating classical and end-to-end hybrid systems for scalability from research to production. Requires 6+ years of experience in production autonomous driving systems, AI foundation models, large-scale ML systems, end-to-end driving models, and robotics/embodied AI system architecture.

NVIDIA is seeking a Solutions Architect to be the lead technical authority for Federal partnerships, focusing on deploying Generative AI at scale for U.S. Government agencies. The role involves architecting and optimizing the 'AI Factory,' leading POCs for NVIDIA's AI software stack, and navigating complex Federal security frameworks. The ideal candidate has extensive experience in full-stack data center architecture, the AI lifecycle (data curation, fine-tuning, inference orchestration), and strategic communication with both technical and leadership audiences within the public sector.

Senior Software Engineer role at NVIDIA focused on building Physical AI systems for humanoid robots. The role involves defining technical direction for generative AI workflows in robotics, spanning simulation, real-world deployment, and continuous learning. Responsibilities include building the humanoid reference platform, integrating NVIDIA products, and providing technical mentorship. Requires significant robotics software engineering experience, with a focus on AI-powered robots and robot learning.

Senior Software Engineer to develop NVIDIA's AI platform, focusing on performance optimizations in deep learning frameworks using JAX. The role involves designing and implementing JAX core components, driving performance on NVIDIA products, and building tools to increase efficiency for AI-based systems.

NVIDIA is seeking an intern to build and maintain AI agent skills, MCP tools, and agentic workflows to automate operations. The role involves developing cloud-native services, data automation pipelines, and interactive dashboards. Candidates should have strong Python skills, experience with AI-powered applications like AI agents and RAG pipelines, and familiarity with cloud-native technologies.

Senior engineer to architect and build an AI-native framework using AI agents for software development, focusing on scaling, performance optimization, and integrating SOTA models for inference.

Solutions Architect role focused on integrating NVIDIA's software and tools with OEM partners' offerings, specifically for AI security and accelerated compute solutions. The role involves designing GPU-accelerated pipelines, developing proof-of-concept technologies, guiding Agentic AI workflows (RAG, GNN), and translating AI/cybersecurity research into deployable architectures for enterprise and government customers.

NVIDIA is seeking an AI Engineer to build AI application-layer services for SOC design automation, including assistants, retrieval, Q&A, workflow automation, and AI agents. The role involves designing, implementing, and operating LLM-backed services, building RAG and knowledge systems, applying agent and orchestration patterns, improving developer experience with AI-assisted coding, and owning reliability and evaluation.

NVIDIA is seeking architects to drive architectural performance for its next-generation AI server systems. This position demands a unique capability to bridge deep architectural knowledge, workload analysis, and hands-on silicon investigations. Candidates should be adept at working directly with silicon, high-level models, and simulators. Responsibilities include conducting performance investigations on both NVIDIA and competitive platforms, and developing targeted microbenchmarks to examine specific architectural aspects. The role does not heavily involve modeling tasks (functional or performance), though occasional focused assignments may arise.

Senior Software Engineer role focused on applying deep learning and computer vision to 3D/4D world modeling for autonomous driving products, involving building reconstruction systems, developing evaluation methods, and optimizing neural network performance.

NVIDIA Developer Technology Engineer focused on optimizing AI workloads, particularly large language models (LLMs), on NVIDIA's GPU platform. The role involves deep dives into application performance, GPU kernel optimization, distributed training and inference, and collaboration with various internal teams and external developers. It requires strong software engineering skills, parallel programming expertise, and a focus on performance analysis and tuning.

Senior Solutions Architect focused on building and optimizing Kubernetes infrastructure for Agentic AI and Agentic RL workloads, working with Cloud Service Providers in China.

NVIDIA is seeking a Senior Architect to lead the development of software infrastructure for AI-driven scientific discovery in chemistry and materials science. The role involves shaping NVIDIA ALCHEMI and its ecosystem, translating AI research (ML interatomic potentials, generative modeling) into product direction, and engaging with internal/external stakeholders. The ideal candidate has a PhD or equivalent experience, 8+ years of AI/ML software development for chemistry/materials, strong GPU computing and ML framework experience, and expertise in scientific software architecture.

Product Manager for AI Frameworks at NVIDIA, focusing on Recommender Systems and Generative Recommendation Models. The role involves building products for frontier RecSys and Generative Recommendation Models on Nvidia systems, enabling researchers and operators, and pushing the boundaries of what is possible in research-to-production. Responsibilities include creating and optimizing pre-training/inference and post-training frameworks, developing product strategy, roadmaps, and go-to-market plans, and collaborating with internal and external customers. Requires experience with training/inference post-training and optimization software, GenAI/ML concepts, large-scale distributed systems, and technical product management.

Internship role focused on building innovative tools and applications in robotics, agentic modeling, and AI model inference, utilizing NVIDIA SDKs and frameworks. Involves AI engineering, optimization, and exploring new trends in AI and computing acceleration.

Develop and deploy AI agents and frameworks for hardware verification tasks, processing codebases and optimizing retrieval/generation algorithms for enterprise data.

NVIDIA is seeking a Senior Infrastructure and Methodology Engineer to optimize chip design workflows by developing AI and agentic applications. The role involves integrating LLM capabilities into various engineering tools, designing agent applications, and establishing evaluation benchmarks. Requires full-stack web development and AI application development experience, with a preference for ASIC knowledge.

Engineering Manager for NVIDIA's Autonomous Vehicles division, leading teams to build and scale AI-native autonomous driving systems, integrating classical safety stacks with foundation models and large-scale AI systems from research to production.

NVIDIA is seeking a Senior Integration Engineer to work on their end-to-end autonomous driving application, focusing on integrating modular software components and optimizing performance on heterogeneous hardware architectures. The role involves defining software architecture for L2/L3/L4 autonomous driving solutions, performing in-vehicle and simulation testing, and developing efficient C++ code using CUDA.

Senior Integration Engineer for NVIDIA's end-to-end autonomous driving application, focusing on integrating software components, optimizing performance, and developing efficient C++ code on heterogeneous hardware architectures (including GPUs) for L2/L3/L4 autonomous driving solutions.

NVIDIA is seeking an AI and FSI Developer Technology Engineer to optimize AI and HPC workloads on NVIDIA GPUs and CPUs, focusing on performance tuning and eliminating bottlenecks for financial markets. The role involves research, development, analysis, and collaboration with experts to improve performance across the stack, from algorithms to kernels. The engineer will also publish and present their work and influence future hardware/software designs.

Senior Software Engineer to build next-generation AI platforms and products, focusing on agentic AI systems, RAG, and scalable infrastructure for enterprise workflows.

NVIDIA is looking for a Solutions Architect to guide partners in building enterprise Physical AI systems using Omniverse, Cosmos, synthetic data, and coding-agent-assisted digital twins workflows. The role involves technical advising on simulation, digital twins, robotics, industrial autonomy, and auto, focusing on architecture, compute, testing, and rollout strategies. Key responsibilities include guiding partners on synthetic data generation, evaluation methods, using coding agents for development acceleration, defining benchmarks, advising on compute infrastructure for simulation and inference, and building reference architectures.

Senior Solutions Architect focused on building LLM inference platforms using NVIDIA GPUs, KV cache, and tiered memory solutions. The role involves technical exploration with customers, performance analysis, and translating customer needs into product roadmaps.

Solutions Architect role at NVIDIA focusing on optimizing LLM inference and training acceleration, contributing to open-source frameworks like SGLang and vLLM, and developing KV cache offloading. Requires strong programming, systems fundamentals, and experience in performance analysis.

NVIDIA Developer Technology Engineer focused on optimizing core parallel algorithms and data structures for GPUs, specifically working with LLM training frameworks and performance optimization. Collaborates with application developers and internal NVIDIA teams to improve performance and developer efficiency.

NVIDIA Solutions Architect focused on optimizing AI inference workloads across CPU, GPU, and LPU platforms for customers. The role involves technical expertise, proof-of-concept development, and optimizing AI efficiency in heterogeneous environments.

Solutions Architect for Financial Services at NVIDIA, focusing on guiding customers in leveraging NVIDIA's AI technologies, particularly in areas like model distillation, domain adaptation, reinforcement learning, and post-training algorithms. The role involves technical advocacy, collaborative innovation, and knowledge sharing within the financial services sector, requiring expertise in AI frameworks, Python, distributed computing, and the AI model lifecycle.

NVIDIA is seeking an AI Chip Design Engineer to develop and integrate AI capabilities into verification tasks. The role involves creating AI agents to enhance productivity, building production infrastructure for these agents, and optimizing algorithms for enterprise data. Requires strong proficiency in LLM libraries, GPU/CPU architectures, and HW verification methodologies.

NVIDIA is seeking an AI Chip Design Engineer to develop and integrate AI capabilities into verification tasks, focusing on building and maintaining infrastructure for AI agents that process large codebases and optimize verification flows. The role involves developing retrieval and generation algorithms, integrating AI optimizations, and working with HW engineering teams.

This role focuses on researching and developing techniques to accelerate AI workloads (deep learning, machine learning) on advanced computer architectures, specifically GPUs. The engineer will perform in-depth analysis and optimization of complex AI and HPC algorithms, publish findings, and influence future hardware/software design. Requires deep C/C++ programming, parallel programming (CUDA, etc.), low-level performance optimization, and CPU/GPU architecture expertise.

Seeking a Principal Developer Technology Engineer to research and develop techniques for GPU acceleration of AI workloads, focusing on performance optimization of deep learning and HPC algorithms on modern CPU and GPU architectures. This role involves collaborating with internal teams and the developer community, influencing hardware/software design, and publishing findings.

Senior AI/ML Performance and Efficiency Engineer focused on optimizing GPU cluster performance for AI/ML researchers by addressing infrastructure and application bottlenecks. This role involves building tools, analyzing efficiency, and collaborating across teams to improve hardware, software, and infrastructure usage for various ML workloads like Robotics, Autonomous vehicles, LLMs, and Videos.

Senior Developer Technology Engineer focused on researching and developing techniques to GPU accelerate AI workloads, optimizing performance on modern CPU and GPU architectures, and collaborating with the developer community and internal teams to influence next-generation hardware and software design.

Senior AI Formal Verification Engineer to enhance in-house formal tools with AI, leveraging LLMs and ML to automate intent-to-proof workflows and debug complex chips. Role involves architecting methodologies, developing AI agents, and creating AI-based debug assistants.

NVIDIA is seeking a Solution Architect with deep expertise in AI solutions to drive the efficient use of compute platforms in the Energy Industry. The role involves being a trusted technical advisor to developers and customers, embedding NVIDIA software, improving application performance, and establishing the foundation for next-generation AI systems. Responsibilities include supporting business development, working directly with customers, assisting in the adoption of NVIDIA software, analyzing architectures for acceleration opportunities, providing feedback to engineering teams, and delivering trainings and demonstrations. Requires an MS/PhD in a technical field, 5+ years of experience in AI/ML/DL/NLP/Generative AI, and 5+ years of industrial experience in power grid software and advanced ML for grid operations. Familiarity with accelerated computing, GPU systems, Python/C/C++, major AI frameworks, containers, and version control is essential. Experience designing and building complex AI/ML solutions, and reasoning across various system components is also required.

NVIDIA is seeking a Senior Tools Development Engineer to build agentic infrastructure for test automation and quality engineering on the Omniverse platform. The role involves designing and deploying multi-agent systems, orchestration frameworks, and evaluation systems to improve software quality and reliability.

Senior Software Engineer at NVIDIA focused on 3D/4D reconstruction for autonomous driving products. The role involves building and optimizing systems using deep learning, computer vision, and generative AI techniques, including large geometry models, Gaussian splatting, and diffusion models. Responsibilities include developing reconstruction systems, inventing evaluation methods, creating visualization tools, building automated workflows, and optimizing neural network performance for training and deployment. The goal is to improve reconstruction fidelity and simulation realism for end-to-end driving models.

Engineering Manager for NVIDIA's AI Developer Technology team, focused on leading a team to optimize and develop algorithms for Deep Learning and Machine Learning applications, influencing next-generation hardware/software, and collaborating with customers and internal teams. The role involves optimizing training and inference performance on NVIDIA hardware.

Senior Developer Technology Engineer focused on researching and optimizing AI/ML workloads for GPU acceleration, involving deep analysis, performance tuning, and collaboration with the developer community and internal teams to influence next-generation hardware and software design.

NVIDIA is seeking an Applied AI Engineer to lead end-to-end solution development for timing and constraint analysis workflows in VLSI/ASIC design. The role involves data generation, model training, orchestration, and building autonomous agents that interact with timing tools. The engineer will develop AI-driven solutions, integrate data sources, implement scalable orchestration, and build interpretable AI pipelines using GNNs, LLMs, and reasoning engines. Experience with Python, PyTorch/TensorFlow, graph/agentic AI frameworks, and EDA tools is required.

Senior AI/MLOps Engineer focused on building and maintaining infrastructure, tools, and processes for the AI lifecycle in a production environment, specifically for security and networking AI models and agents. The role involves optimizing models, deploying agentic systems and LLMs, designing training/inference pipelines, and collaborating with various engineering teams.

Senior Manager for System Software Engineering at NVIDIA, focusing on Metropolis Accelerated and Inferencing Software. The role involves leading engineering teams, driving strategic implementations of inference solutions (TensorRT, VLLM) for edge and enterprise devices, performance benchmarking, and technical leadership in deep learning. Requires extensive experience in machine learning/deep learning, embedded software, GPU/CPU optimization, and multimodal AI systems.

NVIDIA is seeking a Senior Product Architect to design and validate AI storage infrastructure, focusing on optimizing systems for large-scale foundation model training, disaggregated inference, and agentic AI pipelines. The role involves architecting end-to-end reference architectures, defining system-level architectures, and collaborating with partners and customers to deliver proof-of-concepts.

NVIDIA is seeking a Developer Relations Manager to engage with AI-native companies, helping them design, optimize, and scale their AI platforms on NVIDIA technologies. The role involves advising founders and engineering teams on building agentic systems, AI copilots, and multimodal applications, with a focus on accelerating training, optimizing inference, and delivering AI experiences. The ideal candidate has deep technical expertise in AI systems, developer platforms, and large-scale inference infrastructure.

This role focuses on developing and scaling AI platforms for simulation and 3D reconstruction, particularly within the Omniverse ecosystem. The Senior Solutions Architect will act as a technical advisor, prototype solutions, implement intricate technical systems, provide technical enablement, and advocate for partner needs. The role requires expertise in AI, systems knowledge, autonomous systems, simulation, generative AI, Python, C++, DL/RL frameworks, computer vision, and 3D reconstruction.

Manager for an AI team at NVIDIA, focusing on developing and leading the implementation of cutting-edge AI applications including RAG, LLMs, AI Agents, recommendation engines, and classical AI models. The role involves managing a team of 6-8 engineers, providing technical leadership, and collaborating with cross-functional teams to identify and implement AI opportunities.

Senior Software Engineer role focused on building large-scale distributed Vision AI platforms for video analytics using NVIDIA Metropolis. The role involves designing and developing functionalities for video processing, integrating VLMs, CV models, and LLMs, and optimizing performance on NVIDIA hardware. Requires strong software development experience with ML systems, C++, Python, and GPU acceleration.

This role focuses on deploying and optimizing large models using NVIDIA's Inference Microservice (NIM) and related tools. The Solutions Architect will package optimized models (LLM, VLM, etc.) into containers for deployment, refine NIM tools for the community, and design/implement agentic AI solutions for customer scenarios. The role requires strong programming skills, experience with inference engines, and MLOps practices, with a focus on performance engineering and model optimization.

NVIDIA is seeking an AI in Industry Solution Architecture Intern to help optimize large models, develop AI workflows, and deliver advanced AI solutions. The intern will provide technical support, design and implement optimizations for AI models, and set up model training or inference to identify and resolve bottlenecks. This role involves working with various AI models and inference frameworks, conducting research, and collaborating with global teams.

NVIDIA is seeking a Senior Software Engineer for their Isaac Lab team to develop features for a robot learning platform, focusing on reinforcement learning, multi-agent learning, and sim-to-real deployment. The role involves automating workflows, scaling in the cloud, and collaborating with research teams on next-generation robots.

NVIDIA is seeking a Robotics Software Engineering Manager to lead a team focused on sim-first development, real-world deployment, and continuous learning for physical AI robots, such as Humanoid Robots. The role involves hands-on development, implementation, and deployment of real-time software stacks, fostering innovation, and collaborating with cross-functional teams.

NVIDIA is seeking a Senior Solutions Architect for Physical AI to support customers building robotics and Physical AI solutions on NVIDIA’s platforms. This role involves guiding architecture, prototyping, and troubleshooting across robotics deployments from simulation to training to deployment, focusing on applied AI (computer vision, GenAI) for robotics.

Senior Software Engineer to develop production ADAS and autonomous driving functions in C++ and Python, integrating deep learning models into real-time inference pipelines on NVIDIA GPUs for safety-critical automotive applications.

NVIDIA is seeking a Performance Engineer Intern to support performance testing of datacenter products and applications, focusing on AI workloads like LLM training and inference, as well as HPC. The role involves benchmarking, profiling, analyzing performance, developing automation scripts, and collaborating with internal teams. The intern will aggregate and report testing data for sales, marketing, and engineering teams, and assist in developing tools and processes for automated testing.

NVIDIA is seeking a Senior Solutions Architect with expertise in AI Supercomputing to support academic and commercial groups using NVIDIA products for deep learning, data analytics, and scientific simulation. The role involves understanding customer needs, developing solutions, demonstrating workflows, and communicating requirements to NVIDIA Engineering. Requires 3+ years of Deep Learning research experience, experience with LLM training and adaptation, and familiarity with DL frameworks and Generative AI.

NVIDIA is seeking a System Software Architect to research and develop advanced networking solutions for AI data centers, focusing on accelerating AI workloads, inference, and model serving. The role involves enhancing GPU networking offerings, designing optimizations for data movement, and evaluating new technologies.

NVIDIA is seeking a Senior GPU System Architect to design multi-GPU scale-up and scale-out datacenter systems for AI and HPC. The role involves architecting system topologies, defining interconnects (NVLink, Ethernet), collaborating on RDMA, using system models for analysis, and co-designing hardware-software stacks for efficient AI workload deployment.

Senior System Software Engineer role focused on speech AI technologies (ASR, TTS, ALM, S2S) for enterprise and developer customers. Responsibilities include implementing, troubleshooting, and optimizing GPU-accelerated speech systems in production, transitioning models from research to production, optimizing inference performance, developing core speech services using C++ and Python with CUDA, and contributing to client SDKs. Requires strong programming skills, experience with inference pipelines, understanding of modern model architectures, and knowledge of real-time streaming audio and low-latency systems. Experience with speech model fine-tuning is required.

NVIDIA is seeking an experienced Software Engineer to work on their GPU-accelerated Speech AI platform, focusing on building and optimizing core speech recognition (ASR), text-to-speech (TTS), and S2S services for real-time conversational AI applications. The role involves developing C++ & Python backend implementations, optimizing inference performance, adding new features, contributing to client libraries, and performance analysis of complex systems.

Solutions Architect role focused on designing, building, and operationalizing large-scale AI factories and GenAI/Agentic AI solutions for enterprise customers, leveraging NVIDIA's technology stack. This involves hands-on work with compute, networking, software, and cluster management tools.

This role leads complex, cross-functional programs for next-generation generative AI systems, focusing on media content creation. It involves translating research into execution roadmaps, defining program plans, and managing model release readiness across various stages from research to product integration. The role requires strong program management skills in AI/ML and a solid understanding of generative AI systems.

This role focuses on research and development of synthetic data generation and privacy-preserving AI techniques, contributing to open-source libraries within the NVIDIA NeMo ecosystem. It involves building advanced pipelines, researching privacy methods like DP-SGD and NER for PII, and designing software libraries. The role requires a PhD, significant research experience in data privacy and synthetic data, a strong publication record, and expertise in PyTorch, HuggingFace, and LLM inference frameworks.

NVIDIA is seeking an AI Developer Technology Engineer to collaborate with developers, optimize AI workloads on GPUs, research innovative AI techniques, and ensure peak performance on GPU architectures. The role involves developing and optimizing parallel algorithms and data structures, influencing next-gen architectures, and requires proficiency in C++, AI algorithms, and specific domains like multi-modal models or RL for LLMs.

Senior Software Engineer to join the Isaac Lab team, focusing on developing a platform for robot learning, including perception-in-the-loop reinforcement learning, multi-agent/multi-task learning, and VLA & RL integration. The role involves sim-to-real efforts, defining training workflows, and collaborating with research teams to advance humanoid robots.

Senior HPC Performance Engineer focused on optimizing large-scale, CUDA-backed ML training frameworks for AI in Science applications, particularly in digital biology and chemistry. The role involves kernel design, GPU porting, distributed learning, and algorithmic improvements within HPC software stacks.

Software Engineer for NVIDIA's Metropolis Vision AI team, focusing on building and optimizing large-scale distributed Vision AI platforms for real-time and streaming scenarios. The role involves implementing high-performance pipelines, developing distributed services for video/image/3D data processing, enhancing multi-modal perception, using simulation/synthetic data, and profiling GPU-accelerated inference. Requires strong C++/Python, Linux, computer vision, deep learning, and distributed systems experience, with practical experience in PyTorch for training and deployment.

Software Engineer role focused on deep learning for neural 3D reconstruction, involving research, design, implementation, optimization, and deployment of DNN models. The role requires C++, PyTorch, and ML/DL techniques, with a preference for experience in DNN development and network acceleration.

Senior AI Application Developer role focused on developing and deploying scalable GenAI applications to accelerate GPU/SOC architecture modeling. The role involves integrating LLMs into existing workflows, collaborating with hardware architects and infrastructure engineers, and researching emerging AI technologies. Requires proficiency in C++, Python, ML frameworks, and hands-on experience with LLMs and multimodal models.

Senior Performance Compiler Engineer to work on the open-source Triton compiler project, focusing on using compilers to improve AI performance on NVIDIA GPUs for large language models, agents, and other AI applications. The role involves investigating GPU hardware, designing and implementing compiler technology using MLIR to optimize kernel descriptions for efficient GPU code generation, and collaborating with internal teams.

Senior Systems Engineer role focused on integrating AI and traditional rendering techniques for real-time visual experiences. The role involves taking innovative techniques like AlpaDreams and driving them into production-ready, real-time pipelines, owning the end-to-end path from prototype to shipping product, and solving complex systems challenges related to latency, memory, and throughput. Requires deep expertise in graphics and AI, with a strong track record of shipping impactful products and experience with systems-level thinking.

Senior AI Engineer role focused on developing and deploying AI agents and LLM-based solutions to automate software engineering workflows within NVIDIA. The role involves creating tools to improve developer efficiency, accelerate feedback loops, and enhance release reliability, with a focus on predictive modeling for risk identification and leveraging RAG and fine-tuning techniques.

Senior Data and AI Solutions Engineer at NVIDIA to partner with engineering teams, transform data, BI, automation, and agentic AI into measurable engineering productivity gains. Develop and deploy production-grade AI and data solutions, including agentic systems and RAG pipelines, from concept to deployment.

NVIDIA is seeking a Machine Learning Intern to support the development of AI agents for workflow automation and intelligent assistants. The role involves working on conversational AI, LLM applications, RAG systems, and speech AI workflows, building prototypes with NVIDIA AI technologies, and assisting with evaluation and deployment. The ideal candidate is pursuing a degree in a related field, has experience with machine learning, strong Python skills, and familiarity with Linux.

NVIDIA is seeking a Machine Learning Intern to support research and development of large language and multimodal models. The intern will work on model fine-tuning, parameter-efficient training, architecture exploration, experiments, benchmarking, evaluation, data analysis, and prototype development using NVIDIA AI platforms and GPU-accelerated tools. The role also involves collaborating with researchers and engineers on AI innovation projects and exploring opportunities for technical publications.

NVIDIA is seeking a Machine Learning Intern to assist with developing demonstrations using NVIDIA SDKs, algorithmic development, and AI software development. The role involves keeping up with the latest NVIDIA technology, building demos, and engaging the AI community through workshops.

AI Research Engineer/Applied Scientist focused on Compilers/Low-level optimization to develop AI compiler solutions for NVIDIA's software stack and GPU acceleration. Responsibilities include applying AI to compilation, implementing AI-based solutions for GPU programming, building training pipelines (fine-tuning, RL), defining model I/O, developing evaluation frameworks, prompt engineering, integrating learned policies, prototyping models, creating datasets, and applying RL for optimization.

Senior Software AI Engineer to architect, develop, and support end-to-end software tools, focusing on integrating AI/ML solutions and agentic workflows into production systems for hardware platforms. Responsibilities include backend services, data pipelines, and user interfaces, with an emphasis on autonomous reasoning and action.

Distinguished Software Architect role focused on designing and researching next-generation communication libraries and platforms for Deep Learning and High Performance Computing at NVIDIA. The role involves co-designing HW/SW solutions with GPU, Networking, and SW architects, driving adoption of new communication technologies, and keeping up with DL research. Requires deep expertise in HPC, parallel programming, communication runtimes, system/GPU architecture, and networking, with strong programming skills in C/C++.

NVIDIA is seeking a Senior Deep Learning Compiler Engineer to develop compiler optimization algorithms for deep learning networks. This role involves collaborating with deep learning software framework and hardware architecture teams to accelerate next-generation deep learning software, focusing on public APIs, performance, and compiler infrastructure for neural networks.

NVIDIA is seeking a Senior Deep Learning Compiler Verification Engineer to design and build systems for verifying correctness in deep learning compilers, focusing on graph transformations, IR lowering, and GPU execution. The role involves analyzing and validating optimizations, engineering test generation systems using deep learning solutions, and defining quality metrics for evolving models, compiler stacks, and hardware.

Senior Software Engineer to own and evolve CI/CD infrastructure for NVIDIA's deep learning compiler stacks. Responsibilities include designing and operating scalable CI systems for ML workloads, delivering performance signals, and applying AI/agent-based workflows to improve developer efficiency and triage.

Senior System Software Engineer to work on Dynamo-Triton Inference Server, a GPU-accelerated AI inference serving platform. The role involves developing high-performance inference software, contributing to feature development, driving customer adoption, and optimizing throughput and latency for both LLM and non-LLM workloads.

Senior Developer Technology Engineer focused on optimizing AI GPU deployment on the NVIDIA RTX platform for enterprise and consumer AI applications. This role involves profiling, debugging, training, and enhancing open-source LLM and GenAI software on Windows, collaborating with internal teams and external partners to improve performance and user experience.

Senior Software Engineer to build AI and agentic engineering efforts for enterprise systems, focusing on automating workflows by connecting to core systems of record. The role involves designing and developing resilient systems, data integration, and implementing agentic automation using frameworks like LangChain.

This Principal Cyber Security Engineer role focuses on building core agentic identity and security capabilities for AI agents within NVIDIA's internal ecosystem. The role involves architecting and prototyping solutions for agent use cases across various environments, developing reusable tools and APIs, and collaborating with multiple teams to ensure secure and reliable agent operations. It requires strong software engineering, security, and identity expertise, with an emphasis on practical, production-ready systems.

NVIDIA is seeking a Deep Learning Kernel Software Performance Architect to develop and analyze processor and system architectures that accelerate machine learning and data analytics applications. The role involves debugging deep learning software, developing analysis tools, and collaborating with various NVIDIA teams to optimize performance.

NVIDIA is seeking a Solutions Architect to deploy and enhance AI inference solutions at scale using GPU technology and Kubernetes. The role involves building inference pipelines, orchestrating disaggregated inference, accelerating inference with various backends, and providing technical leadership to customers for enterprise AI deployments.

NVIDIA is seeking an Autonomous Vehicle Performance Architecture Engineer to design, model, and verify state-of-the-art programmable vision accelerators (PVA) for automotive and robotics. The role involves optimizing software for autonomous driving solutions, analyzing and prototyping applications, building performance models for future architectures, and collaborating with teams to enhance PVA architecture. Requires a Masters/PhD, 3+ years of relevant experience, strong C/C++ and computer architecture skills, and performance modeling/optimization expertise. Experience in DSP programming, autonomous vehicle software, deep learning, computer vision, and self-driving cars is a plus.

Senior Software Engineer focused on optimizing and scaling AI inference for large language models, working with customers and contributing to open-source projects like vLLM.

Senior Software Engineer role focused on designing and implementing inference software optimizations for NVIDIA TensorRT and TensorRT-LLM to accelerate AI applications on NVIDIA GPUs. Involves C++, Python, and CUDA development, collaboration with AI experts, and optimization of deep learning frameworks and compilers.

NVIDIA is seeking engineers to develop algorithms and optimizations for their LPX inference and compiler stack, working at the intersection of large-scale systems, compilers, and deep learning to map neural network workloads onto future NVIDIA platforms. Responsibilities include building and maintaining high-performance runtime and compiler components for end-to-end inference optimization, defining workload mappings, extending the SW ecosystem, benchmarking, profiling, and collaborating with hardware architects. The role involves prototyping new compilation and runtime techniques and publishing technical work.

Senior Manager, Software Engineering at NVIDIA focused on leading a team to design and deliver enterprise-grade agentic AI solutions, including LLM-based agents, RAG, and orchestration, with a strong emphasis on full-stack ownership, automation, and roadmap definition.

NVIDIA is seeking a Senior HPC Cluster Administrator to manage large-scale GPU compute clusters for deep learning training, inference, and HPC workloads. The role involves full lifecycle management, automation, performance optimization, and collaboration with ML engineers and software teams.

Senior Solutions Architect focused on deploying Generative AI and LLMs, optimizing inference performance on Kubernetes, and collaborating with customers and internal teams on NVIDIA's AI platforms.

Principal Software Engineer to lead the development and hardening of agentic AI applications and infrastructure within NVIDIA's Enterprise AI team. This role focuses on improving reliability, performance, and scalability of AI products, designing resilient systems, establishing operational excellence, and building reusable capabilities for agent domains. The position requires deep expertise in production software systems, full-stack development, and modern AI application patterns, with a strong emphasis on turning prototypes into mature, well-operated production systems.

Senior Deep Learning Test Development Engineer (SDET) at NVIDIA's AI SWQA team, responsible for validating the robustness and performance of NVIDIA's AI software and GPU Infrastructure across various AI scenarios. The role involves test planning, design, execution, automation, and bug management, with a focus on improving workflow processes and efficiency. Experience with LLM inference frameworks and AI development tools is required.

Software Engineer role focused on developing AI and LLM-based solutions to enhance chip design and verification processes. Requires 5+ years of software development experience with at least 2 years in AI/LLM solutions.

Senior Staff AI Platform Engineer at NVIDIA responsible for building, supporting, and maintaining AI-native infrastructure for enterprise products. This role involves architecting and scaling LLM/ML infrastructure, designing observability for AI models, developing automation, and troubleshooting complex distributed systems. The engineer will also drive AI-assisted engineering practices and partner with product teams to deliver scalable AI solutions.

Senior Manager, Machine Learning Ops Engineering - Automotive at NVIDIA, leading the development and operation of large-scale data and ML pipelines for autonomous driving, focusing on data ingestion, processing, and validation for training and evaluation datasets.

This role is for a Senior Technical Program Manager at NVIDIA, focused on building and scaling AI-powered infrastructure for hardware and silicon development. The TPM will drive cross-functional programs to integrate AI capabilities like chatbots and agents into chip design, verification, and production workflows, collaborating with AI engineers, hardware teams, and platform groups. The role emphasizes influencing technical direction and delivering AI systems that transform engineering processes.

Senior Engineer focused on Deep Learning Compiler Verification and Infrastructure at NVIDIA. The role involves implementing compiler verification software and related infrastructure to accelerate deep learning workloads, working closely with compiler developers on functional and performance testing, and applying deep learning techniques to verification solutions.

Senior Software Engineer focused on developing high-performance deep learning inference software for safety-critical automotive applications using C++. The role involves integrating hardware functionalities into TensorRT, optimizing performance, and ensuring rigorous safety validation and documentation.

NVIDIA is seeking a Senior Software Engineer to develop and scale a state-of-the-art inference framework for accelerating Deep Learning models, particularly LLMs, on NVIDIA GPUs using TensorRT. The role involves crafting inferencing software, developing components of TensorRT, and optimizing the deployment of trained models using C++ and Python.

The Validation Data Scientist will build tooling, perform large-scale analysis, and drive data-driven evaluation of vehicle-level behavior and Operational Design Domain (ODD) coverage during scaled testing for autonomous vehicles. This role involves building and improving evaluation frameworks, data pipelines, and data curation strategies, defining core metrics, and automating scalable workflows using cloud platforms and AI. The goal is to influence product development, technical reviews, and software releases by providing quantitative analyses and clear reporting.

NVIDIA is seeking a Validation Data Engineer for its Autonomous Vehicles team. The role involves building tooling, performing large-scale analysis, and driving data-driven evaluation of vehicle-level behavior and ODD coverage using real-world and virtual AV driving logs. Responsibilities include implementing evaluation frameworks, data pipelines, and data curation strategies, defining core metrics, and contributing to scalable workflows using cloud platforms and AI. The ideal candidate has 5+ years of experience in data engineering or analytics, strong Python skills, and experience with autonomous vehicle behavior analysis.

NVIDIA is seeking a Senior Software Test Development Engineer for its AI SWQA team. This role involves defining, developing, and executing tests to validate the robustness and performance of NVIDIA's AI software and GPU infrastructure across various AI applications like autonomous driving, healthcare, and NLP. The engineer will collaborate with AI product teams, develop complex test plans, manage bug lifecycles, and automate test cases for CI/CD pipelines. The position requires a Master's degree, 5+ years of QA/test automation experience, strong Python skills, and direct experience with AI tools/products or using AI for major features. Experience with AI for QA automation and deep learning frameworks is a plus.

Senior Engineer focused on building and improving release automation for AI/ML systems, specifically within the Neural Graphics domain. The role involves driving the adoption of AI and agentic workflows into the team's development and release processes, ensuring product security, licensing compliance, and quality. Key responsibilities include creating repeatable packaging and publishing flows, and acting as a bridge between core agentic workflow teams and the NuRec team.

NVIDIA is seeking a Senior Software Test Development Engineer for their Deep Learning SWQA team. This role involves defining, developing, and executing tests to validate the robustness and performance of NVIDIA's Deep Learning software and GPU infrastructure across various AI applications. Responsibilities include collaborating with AI product teams, developing complex test plans, automating test cases, and managing the bug lifecycle. The ideal candidate has 6+ years of QA/test automation experience, scripting skills, C/C++ development, and understanding of Deep Learning frameworks and models, particularly in end-to-end customer scenarios.

NVIDIA is seeking a Senior AI Inference Compiler Engineer to develop compiler IR, programming models, and optimizations for future GPU architectures, focusing on delivering leading inference performance for deep learning models. The role involves collaborating with deep learning software framework and hardware architecture teams to accelerate next-generation AI software, defining APIs, optimizing performance, and generating kernels for neural networks.

This role focuses on building and maintaining CI/CD pipelines and release processes for NVIDIA's GenAI frameworks (Megatron-LM, NeMo). It involves implementing scalable DevOps solutions, managing infrastructure (Kubernetes, Docker, Slurm), automating tasks for research and development cycles, and developing quality control measures. The goal is to enable efficient work for GenAI software engineers, DL algorithm engineers, and research scientists, optimizing performance and ensuring high-quality software delivery.

Senior QA Automation Engineer for NVIDIA's Network AI platform team, focusing on testing AI/ML-powered network solutions, including AI algorithms and multi-cloud integrations for enterprise-scale network monitoring and automation. Requires strong Python automation, networking knowledge, and experience with API and system testing.

System Software Engineer role at NVIDIA focused on deep learning, data analytics, and machine learning. The role involves researching, prototyping, developing, and optimizing solutions, tools, and libraries. It also includes analyzing and improving deep learning libraries and frameworks, defining APIs, and performance tuning. The position requires strong Python and C/C++ programming skills, experience in complex system design, and knowledge of algorithms and data structures. The role is primarily focused on the engineering and optimization of AI infrastructure and tools.

Solutions Architect role focused on integrating NVIDIA's AI software and tools with OEM partners' offerings, particularly in AI data pipelines and Agentic AI workflows for threat detection. Requires expertise in GPU-accelerated data processing, machine learning, and big data frameworks.

NVIDIA's Robotics Platform is building the software and hardware systems for intelligent machines, focusing on foundational compute stacks and AI sensor processing frameworks. The role involves designing, building, and optimizing core platform features, developer APIs, reference applications, and tooling for performance, observability, and debugging, with an emphasis on leveraging NVIDIA hardware and using agentic AI for development acceleration.

Senior Data Scientist role focused on building production systems to analyze unstructured customer feedback and telemetry data for root-cause analysis, anomaly detection, and prediction of churn/capacity needs in the GeForce NOW cloud gaming service. The role involves end-to-end data product lifecycle, from data pipelines to algorithm deployment and system ownership.

Senior Deep Learning Systems Engineer focused on analyzing and optimizing the performance and power consumption of deep learning applications on datacenter hardware, influencing the design of future AI systems and software stacks. This role involves developing software infrastructure, analysis tools, and profiling methodologies for DL workloads, with a strong emphasis on system architecture and performance analysis.

NVIDIA is seeking a Senior HPC and AI Operation Engineer to manage and maintain large-scale HPC/AI clusters, including job scheduling, CI/CD pipelines, and troubleshooting from bare metal to application level. The role involves supporting R&D activities and engaging in POCs, requiring strong Linux administration, scripting, and knowledge of HPC/AI technologies, storage, and networking.

NVIDIA is seeking a Senior Developer Relations Manager to engage with the China industrial and research community, focusing on integrating GPU-accelerated computing solutions, particularly in Generative AI, Agentic AI, and AI Storage. The role involves understanding community requirements, promoting NVIDIA tools, architecting solutions, and driving adoption of new products within the AI storage ecosystem.

Develops internal profiling, analysis, debugging, benchmarking, and simulation tools for AI workloads running on GPU clusters, supporting AI researchers and SW/HW teams to improve performance and efficiency.

Senior Developer Technology Engineer focused on optimizing and deploying AI/GenAI applications on NVIDIA RTX platforms, particularly LLMs on Windows. This role involves working with internal teams and external developers, analyzing performance, conducting training, and improving user experience with OSS software like Llama.cpp and Ollama. Collaboration with driver and architecture teams is key to influencing future GPU features.

Senior Deep Learning Tools Engineer at NVIDIA focused on performance validation, analysis, and tracking for AI workloads accelerated by CUDA Tile compiler technologies and GPU systems. The role involves designing and developing performance testing frameworks, building automated CI/CD pipelines, implementing benchmarking systems, analyzing performance trends, and collaborating with compiler and architecture teams to resolve performance issues. Requires strong programming skills in Python, experience with CI/CD, deep learning frameworks, and hardware-aware performance analysis.

NVIDIA is seeking a Solutions Architect for Financial Services to act as a trusted technical advisor to customers, enabling their productivity and driving adoption of NVIDIA's AI technologies. The role involves working with financial institutions, providing technical guidance, developing solution prototypes, and staying updated on industry trends. Requires a BS/MS/PhD in a technical field, 5+ years of AI experience, financial services background, and expertise in coding for NVIDIA GPUs.

Senior Systems Software Engineer focused on GPU performance at scale for AI workloads, involving collaboration with various hardware and software teams to optimize large-scale computing platforms and deliver insights into AI workload performance.

Solution Architect with deep expertise in AI solutions for the Energy Industry, focusing on efficient use of compute platforms. The role involves being a trusted technical advisor, embedding NVIDIA software into customer architectures, improving application performance, and establishing foundations for next-gen AI systems. Responsibilities include supporting business development, working directly with developers and customers, analyzing architectures for acceleration, providing feedback to engineering/product/research, and delivering trainings/hackathons.

Senior Staff Software Engineer to build and scale the infrastructure for NVIDIA's AI agent ecosystem, focusing on platform services for the full agent lifecycle, Kubernetes execution environments, CI/CD pipelines, and AI data platform components.

Director of Software Engineering at NVIDIA to lead a team building employee-facing AI products, focusing on AI-first experiences and leveraging AI agents.

NVIDIA is seeking engineers to develop algorithms and optimizations for their LPX inference and compiler stack, working at the intersection of large-scale systems, compilers, and deep learning to optimize how neural network workloads map onto future NVIDIA platforms.

Manager for a Systems Software Engineering team focused on NVLink and AI, developing solutions for data center platforms and debugging complex issues using LLMs and agentic AI.

Senior Software Developer to work on an open-source AI networking acceleration library, focusing on performance-oriented low-level infrastructure for inference, utilizing hardware offloads, GPU Kernels, and RDMA. Requires strong C++/C/Rust, Linux, and networking stack knowledge, with advantages in LLM inference, distributed storage, Linux internals, CUDA, and parallel programming.

NVIDIA is seeking a Senior AI Frameworks Engineer to contribute to the CUTLASS project, focusing on developing a Pythonic interface for high-performance GPU computations. The role involves designing APIs, building compilation infrastructure, optimizing developer experience, and managing production-grade delivery for the open-source community.

NVIDIA is seeking a Senior Compiler Engineer with expertise in machine learning and compiler technologies to focus on applied AI and ML within compilers and development tools. The role involves working with Python, C/C++, Julia, and Lisp/Scheme, with a strong foundation in compilers, code generation, and GPU architecture. Experience with LLVM is a plus.

NVIDIA is seeking a Senior Developer Relations Manager to foster strategic partnerships with ISVs developing AgentOps platforms and services. This role involves evangelizing NVIDIA's accelerated computing and AI technologies, managing partner relations, driving technical integration, and influencing NVIDIA's product roadmap based on partner feedback. The ideal candidate has a strong technical background in MLOps, LLMOps, GenAIOps, AgentOps, generative AI, agentic AI, and accelerated computing, along with strategic market understanding and ecosystem development experience.

Product Manager for local AI and agents on Linux for enterprise, focusing on defining agent use cases, owning the product strategy for Linux developer experience, and collaborating with inference backend teams. Requires strong AI/ML and developer tools experience, with a focus on enterprise deployments and modern AI workflows.

NVIDIA is seeking a Senior Sensor Fusion Engineer for their Autonomous Vehicles team. The role involves developing core functionality for autonomous driving by fusing perception DNN and map signals to generate a real-time 3D world model. Responsibilities include enabling L3 autonomy, building fused obstacle and occupancy grids, and providing technical leadership. The position requires significant experience in AV or robotics, with a focus on sensor fusion and real-time systems.

This role is for a Software Engineering Manager to lead a team focused on building AI/LLM-powered infrastructure and tooling for the SONiC Network OS development lifecycle. The team will develop LLM-based tools for failure analysis, test coverage generation, and accelerating product quality, aiming to improve regression analysis and test efficiency.

Product Manager for NVIDIA's AIOps software product, focusing on AI Factories. The role involves defining product strategy, working with engineering, sales, and marketing, and driving customer adoption using AI and agentic techniques to build a scalable platform.

NVIDIA is seeking a Senior Solutions Architect with expertise in AI and professional graphics workflows to support key customers and partners. The role involves understanding customer needs, guiding them to optimal NVIDIA hardware and software solutions, and contributing to knowledge sharing through demos, proof-of-concepts, and technical writing. The position requires strong foundational knowledge in computer science or hardware engineering, extensive software development experience, and familiarity with AI workflows, CUDA, and agentic AI.

Manager for Next-Generation AI Cluster Architecture at NVIDIA, focusing on developing and leading teams to build large-scale AI supercomputing systems, including GPU cluster architectures, networking, and system software. The role involves authoring reference architectures and collaborating on system bring-up and integration.

Manager to lead a team developing and validating next-generation NVIDIA AI supercomputing systems, integrating new compute, networking, storage, and software. Focus on building a platform for software development, automation, and performance engineering, and supporting large-scale deployments for AI and HPC.

NVIDIA is seeking a New College Grad Datacenter GPU Power Architect to contribute to the research and development of energy-efficient GPU and SOC architectures. The role involves developing power estimation models and tools, exploring energy efficiency at GPU and Datacenter levels, and deploying machine learning techniques to model GPU, CPU, Switch, and platform performance and power. The candidate will understand GenAI/HPC workload characteristics to drive HW/SW features for Perf@Watt improvements.

NVIDIA is seeking an AI-first Program Manager to lead and expand its Sustainability Series. This role involves developing and overseeing AI agents and automated workflows for program operations, including research, reporting, and partner intelligence. The position also includes managing the FOSS Fund and Contribution Sprint programs, with a focus on scaling these initiatives through AI-driven automation and system building.

Senior System Software Engineer role focused on building the Physical AI platform for NVIDIA's robotics projects. Responsibilities include robot bring-up, developing auto-verification pipelines, and supporting R&D. The role requires strong robotics software engineering skills, experience with various robot embodiments, and familiarity with AI/ML algorithms for robotics. The engineer will deploy and test software on physical robots and digital twins, and use agentic AI for software development.

Senior Software Engineer focused on developing and executing software-driven characterization workflows for AI workloads on NVIDIA rack-scale systems. The role involves analyzing, characterizing, and optimizing power, performance, and drive behavior across the full stack, including GPUs, CPUs, networking, and system software. Key responsibilities include building automated frameworks for data collection and analysis, investigating system behavior, and supporting new platform bring-up.

NVIDIA is seeking a Senior AI Compiler Engineer to develop compiler optimization algorithms for AI workloads, focusing on delivering leading inference performance on GPUs. The role involves analyzing deep learning networks, optimizing compiler techniques, and working with CUDA and various compiler technologies.

Senior Software Engineer to build and maintain GPU clusters for internal AI researchers, focusing on reliability, performance, and self-service. The role involves engineering solutions for cluster validation, monitoring, and operation, with an emphasis on AIOps and Agentic AI to reduce operational toil.

NVIDIA is seeking a Senior Software Engineer, Test for their Autonomous Vehicles team. The role involves developing and productizing autonomous vehicle solutions, focusing on building and scaling simulation environments for evaluating vehicle performance. The engineer will lead efforts in automating simulation tests, developing reliable infrastructure, and analyzing complex technical issues. Experience with ADAS, Autonomous Driving, Replay testing, or Simulation environments is required, along with strong Python/C++ skills. Experience with AI/ML systems or robotics simulation is a plus.

Senior Technical Product Manager at NVIDIA focused on AI Infrastructure, driving the roadmap for Enterprise Infrastructure products like NVIDIA DGX and Networking. The role involves defining product strategy, creating go-to-market collateral, and engaging with customers and internal teams to improve AI developer efficiency and data center solutions. Requires deep understanding of AI/ML infrastructure, HPC, cloud technologies, and AI/ML concepts like LLMs and Gen AI.

Lead Software Engineer for NVIDIA's Robotics Platform, focusing on end-to-end solutions for training, simulation, and deployment of Physical AI on robots. The role involves leading development of core platform features, building reference integrations, and optimizing for NVIDIA hardware, with an emphasis on performance, reliability, and leveraging AI for development acceleration.

Senior Solutions Architect role at NVIDIA focused on architecting and scaling AI infrastructure, particularly GPU-based systems for deep learning inference, for customers. The role involves technical customer engagement, supporting sales, and providing onsite support.

Software Engineer role focused on developing developer tools for NVIDIA GPUs, specifically bridging AI and graphics for next-generation workflows. The role involves improving existing tools, creating new ones, and collaborating with research and architecture teams to enhance rendering performance and visual quality using AI techniques.

Principal Software Engineer for NVIDIA's DGX Cloud team, focusing on building and scaling foundational systems for high-performance GPU infrastructure. The role involves leading the development of next-generation APIs, state management, and workflow orchestration systems to automate fleet lifecycle operations at scale, integrating AI schedulers and observability tools.

Senior Software Developer focused on AI Networking at NVIDIA, developing communication frameworks, production tools, and benchmarks for large-scale AI training and inference systems. The role involves enabling new AI models, analyzing workloads, designing automation, and collaborating with hardware teams.

NVIDIA is seeking a Lead SoC Product Architect for their Telecom AI RAN platform, focusing on defining the architecture and roadmap for radio and distributed unit products. The role involves analyzing workloads, driving competitive analysis, synthesizing customer requirements, and collaborating with engineering teams to ensure efficient implementation of AI-native RAN applications. The ideal candidate will have extensive experience in wireless RAN/baseband architecture or SoC product definition, with a strong understanding of 3GPP RAN standards and L1/PHY algorithms.

NVIDIA is seeking an AI Developer Technology Engineer to enhance embodied AI responsibilities, develop on products like IsaacSim and Isaac Lab, profile and optimize GPU-based physics simulator performance, and collaborate with various teams to invent next-generation architectures and software platforms. Requires experience with C++, CUDA, Python, Linux, physics simulators, and prior involvement with embodied AI or humanoid robotics firms.

Senior ASIC Infrastructure Engineer at NVIDIA, focusing on defining and deploying AI/ML applications to enhance chip design, debug, and verification processes. The role involves collaborating with hardware design teams, architecting AI/LLM solutions, and staying updated on AI/ML advancements.

NVIDIA is seeking a Principal ISP Architect to lead the development of camera imaging technologies for AI applications in autonomous driving and robotics. The role involves driving innovation in image processing algorithms, including AI methods, and developing ISP architecture specifications. The position requires a Master's or Ph.D. with 12+ years of experience in ISP architecture and imaging science, proficiency in C/C++, MATLAB, Python, and DL frameworks, and experience with AI-based ISP technologies in real-time systems.

This role involves acting as a technical advisor and driver for customers and partners in designing, implementing, and deploying large-scale AI/HPC GPU infrastructure and applications. It focuses on integrating libraries, frameworks, and models, and delivering GenAI, AI, and ML solutions to production, with practical expertise in fine-tuning and deploying models.

Senior Software Test Engineer for L3 and L4 autonomous driving products at NVIDIA. Responsibilities include developing test strategy, defining test plans, formulating test cases, collaborating with stakeholders, leading vehicle integration, and spearheading data triage and root cause analysis. Requires extensive experience in ADAS, system analysis, data analysis, software architecture, and mass-production launches of autonomous driving features, with a strong understanding of functional safety and AV sensor suites.

Senior Software Performance Engineer for Autonomous Vehicles platform, focusing on optimizing latency and throughput of L2/L3/L4 autonomous driving solutions on NVIDIA's heterogeneous hardware architectures. Requires strong C++ skills, parallel programming, performance analysis, and experience with GPGPU/CUDA.

Senior Software Engineer focused on building ML productivity tooling and CI/CD frameworks for robotics research, specifically for humanoid robots and foundation models. The role involves developing visualization tools, applying AI agents to improve programming efficiency, and collaborating with researchers to deliver full-stack solutions.

Senior System Software Engineer focused on optimizing neural graphics performance, specifically Gaussian Splatting and neural reconstruction algorithms, for applications in robotics, healthcare, and AV development. The role involves implementing and optimizing reconstruction/rendering algorithms using CUDA and Slang, optimizing data processing pipelines, and influencing software architecture for performance.

Senior Solutions Architect role focused on integrating and deploying scalable solutions for autonomous vehicles using NVIDIA's platform. Responsibilities include leading vehicle software integration, driving use case analysis, defining requirements, and optimizing processing pipelines. Requires strong C/C++, Python, system performance evaluation, and experience with automotive design processes and standards.

Senior Software Engineer role at NVIDIA focused on autonomous vehicle software, specifically Active Safety features and intervention logic. The role involves adapting NVIDIA Drive software, triaging and diagnosing complex issues in ADAS and autonomous driving systems, collaborating with teams to root cause problems, and supporting vehicle bring-up and validation. Requires strong background in ADAS development, proficiency in embedded environments, and understanding of Active Safety functions. Experience with C++, Python, sensor-based automotive software, and Euro NCAP protocols is advantageous.

Engineering leader to productize neural simulation technologies (AlpaDreams, AlpaSim) for AV and robotics, building a team and scaling an open-source platform by integrating research findings into a modular, production-ready system.

Developer Relations Manager for NVIDIA's Federal Government sector, focusing on autonomous drone systems. The role involves technical engagement with ISVs, primes, and venture-backed companies to promote NVIDIA's accelerated computing stack for edge inference, multi-agent coordination, and synthetic training environments. Requires deep technical credibility in robotics, onboard autonomy, or flight software, with a proven record of influencing partner roadmaps and delivering on DoD timelines.

Internship role focused on developing performance optimizations for deep learning frameworks using JAX, contributing to core components and tools for the NVIDIA AI platform.

This role focuses on designing, implementing, and managing large-scale GPU compute clusters for AI/ML and HPC workloads. It involves infrastructure engineering, automation, and supporting researchers with performance analysis and optimization. The role requires expertise in cluster management, Linux administration, container technologies, scripting, and MPI workflows.

Senior Software Development Engineer to develop key features for NVIDIA's autonomous driving platform, focusing on Trajectory planning and Motion Planning problems. The role involves leading the entire feature lifecycle from design to production, modeling vehicle behaviors, integrating perception and prediction data, and optimizing solver performance.

Manager for a systems and networking engineering team focused on building distributed AI communication systems (libraries, frameworks, system integrations) for GPUs, nodes, and storage. The role involves setting technical direction, leading execution, and fostering technical excellence within the team, with a focus on AI infrastructure problems.

Senior Formal Verification Engineer for GPU Kernels at NVIDIA. The role focuses on developing verification tools that combine formal methods and AI to ensure the correctness of performance-critical GPU kernels, enabling their use in safety-critical systems. Responsibilities include designing and implementing new verification approaches, integrating AI into formal verification workflows, and building agents for task automation.

NVIDIA Developer Technology Engineer focused on optimizing deep learning and machine learning workloads on NVIDIA's accelerated computing platform (GPU, CPU, DPU) for key customers. Requires strong C/C++ and CUDA experience, with an MS/PhD in CS or related field.

Manager of Solutions Architecture focused on leading a team to consult, optimize, and improve the resiliency of customer AI factory infrastructures, including GPU-accelerated systems and AI workloads. The role involves hands-on infrastructure analysis, tuning, and establishing optimization/monitoring methodologies for large-scale AI/HPC systems.

Senior Performance Engineer at NVIDIA focusing on optimizing AI and HPC workloads on GPU/CPU clusters. Responsibilities include profiling, benchmarking, identifying bottlenecks, and developing performance analysis tools, with a strong emphasis on high-performance networking and telemetry.

SWQA Test Developer for embedded systems in AI, Retail, Healthcare, Media, Finance. Role involves using AI tools for QA automation, CI/CD, bug fixing, and building/automating workflows/agents. Also involves training/fine-tuning models for agent optimization and developing tests for embedded/GPU systems. Requires Python/C++ skills, Linux, and knowledge of Docker/cloud platforms.

This role focuses on building and optimizing systems-level software for high-performance communication and memory management libraries essential for distributed AI workloads. It involves hardware-software co-optimization, profiling data movement, and integrating networking capabilities into AI serving stacks, bridging applied research and production engineering.

NVIDIA is seeking a Senior Cloud Infrastructure and DevOps Solutions Architect to advise on and guide the implementation of large-scale computational and AI infrastructure, focusing on Kubernetes-based platforms and automation for AI/HPC systems.

Principal Software Engineer to lead engineering efforts in transforming enterprise systems with AI-infused automated solutions. This role involves architecting and delivering enterprise-grade AI applications and workflow platforms, building resilient end-to-end systems, and developing data integration capabilities for AI applications. Key responsibilities include building agentic workflow automation, defining agent interactions, and supporting orchestration patterns using frameworks like LangChain and LangGraph, while also operationalizing NVIDIA AI technologies.

Senior Software Engineer role focused on shaping the future of autonomous machines and building/deploying scalable robotic solutions, with a focus on humanoid robotics. Responsibilities include crafting application software architecture, scaling deployment of new technologies, integrating hardware/software, and providing technical guidance. Requires experience in robotics, ML/RL, and software development, with a strong plus for GPU programming/CUDA and sim-to-real transfer.

Senior Data Analysis Engineer role focused on critical metrics for autonomous driving (AD) products. The role involves defining performance, supervising test events, analyzing trends, improving triage efficiency, and automating metric generation for dashboards. It requires strong technical ability, scripting experience, and leadership to support AV software development and release.

NVIDIA Solutions Architect focused on AdTech and Media, helping customers adopt NVIDIA's full-stack accelerated computing platform. This role involves technical advisory, proof-of-concept evaluations, deep analysis and optimization of AI/ML models and recommender systems, and translating customer feedback into product insights. The role requires strong Python/C++ coding, understanding of AdTech/MarTech, ML/DL frameworks, and deploying models at scale on cloud or on-premise environments.

This role focuses on designing, building, and maintaining large-scale HPC and AI infrastructure, specifically CPU-based solutions within the NVIDIA AI Factory. The Solutions Architect will enable customers in adopting end-to-end AI solutions, operationalizing large compute resources, and overcoming adoption barriers. The role involves deep technical understanding of NVIDIA's stacks and AI workflows.

This role focuses on designing and implementing AI infrastructure solutions for customers, with a strong emphasis on AI inference at scale and physical AI simulations. It involves full-stack design, including hardware, workload orchestration, and application performance tuning, for hybrid cloud and on-prem deployments.

Senior Software Engineer focused on building and optimizing scalable software automation systems with AI/ML integration for NVIDIA's Data Center environments. The role involves developing automation and validation tools, improving system performance, and troubleshooting complex issues in distributed systems.

Senior Software Test Lead for L3 and L4 autonomous driving products at NVIDIA. Develops test strategy, defines test plans, formulates test cases, and leads integration and validation efforts. Requires extensive experience in ADAS, software architecture, and autonomous vehicle development, with a strong understanding of functional safety and validation methodologies.

Solutions Architect role focused on engaging with customers and partners to support applications and platforms leveraging NVIDIA technology in HPC, ML, AI Physics, Foundation Modeling, and Agentic AI. Requires technical expertise, communication skills, and experience with modern AI architectures.

NVIDIA is seeking a Senior Solutions Architect to advise partners on deploying large-scale AI/HPC GPU infrastructure, integrating libraries, frameworks, and models, and delivering GenAI/AI/ML solutions to production. The role involves end-to-end technology solution integration and providing product strategy recommendations.

Senior Solutions Architect for Financial Services Banking at NVIDIA, focusing on accelerating High-Performance Computing and AI workloads. The role involves partnering with engineering, product, and sales teams, performing proof-of-concepts, optimizing ML/DL models on GPU architectures, and building collateral for finance industry use cases. Requires deep experience in ML/DL algorithms, frameworks, and deploying models at scale.

NVIDIA Solutions Architect focused on enabling cloud partners to achieve elite performance and reliability for AI workloads, particularly LLM training and inference, by adopting reference architectures and optimizing GPU clusters.

Senior Software Engineer role focused on designing, implementing, and maintaining highly-optimized communication runtimes for Deep Learning frameworks and HPC programming interfaces on GPU clusters. This involves system software development, parallel programming interface contributions, and proof-of-concept creation for new designs and hardware features.

NVIDIA is seeking a Senior ASIC Infrastructure Engineer to define and deploy AI/ML applications for chip design, debug, and verification. The role involves collaborating with hardware design teams, architecting novel tools, and staying updated on AI/ML advancements like LLMs, RAG, and GenAI to integrate them into the company's infrastructure.

Manager for a team of infrastructure experts focused on delivering NVIDIA-powered AI Factories, advising partners on large-scale AI/HPC projects, and understanding AI workloads in relation to data center infrastructure.

This role focuses on designing, building, and operationalizing large-scale AI solutions, specifically Agentic AI, for customers through partners. It involves leveraging NVIDIA's technology stacks, including compute, networking, and software, to deploy AI factories and solve complex industry problems. The role requires strong expertise in HPC, AI clusters, and cloud-native methodologies, with a blend of technical guidance, proof-of-concept assistance, and knowledge sharing.

NVIDIA is seeking a Senior Solutions Architect for Financial Services Capital Markets to work with clients on High-Performance Computing and AI workloads. The role involves performing proof-of-concepts, optimizing ML/DL models on GPU architectures, and building collateral for finance industry use cases. Requires strong Python/C++ coding, experience with ML frameworks, and deploying models at scale.

Senior Solutions Architect focused on simulation and AI platforms, specifically 3D Neural Reconstruction and Generative Video models. The role involves prototyping, implementing technical solutions with partners, providing technical enablement, and advocating for partner needs within NVIDIA. Key responsibilities include guiding research in 3D reconstruction and integrating innovations into autonomous simulation pipelines.

Senior Software Solutions Architect at NVIDIA, focusing on helping customers deploy and integrate NVIDIA's AI and machine learning software stacks (like NVIDIA AI, Run:ai, Mission Control) into their existing MLOps environments. This involves collaborating with infrastructure admins, data scientists, and ML engineers, developing integration scripts, diagnosing performance issues, and improving deep learning model performance within cloud-native environments.

Senior Software Triage Engineer for Autonomous Vehicles at NVIDIA, focusing on debugging, root cause analysis, and improving the quality of AV software through triage and evaluation.

Senior Manager of Site Reliability Engineering to lead and reshape IT operations at scale, building AI-powered systems for reliability, speed, and employee experience. Focuses on transforming Incident, Problem, and Change Management using observability, AI insights, and orchestration to move towards predictive and autonomous operations.

Senior Software Engineer role focused on the integration, testing, and sign-off of NVIDIA's Autonomous Vehicles (AV) Drive-Alpha solution, which is powered by AI and accelerated computing. The role involves providing technical feedback on the SW stack's quality, identifying and fixing weak links, driving the RCCA process for continuous improvement, and coordinating efforts across multiple collaborators and component teams. The engineer will also contribute production-quality code when necessary.

Senior Software Engineer for Autonomous Vehicles at NVIDIA, focusing on integrating ML and classical trajectory planners within a safety-oriented framework for SAE Level 3/4 autonomy. The role involves architectural work, establishing safety frameworks, building minimum-risk planning, and designing scalable architectures for self-driving products.

Senior Software Systems Engineer role focused on L3 and L4 autonomous driving products at NVIDIA. Responsibilities include developing use cases, system requirements, performance analysis, formulating test cases, and defining test strategies. Requires strong experience in safety-critical systems engineering, SOTIF, functional safety, and understanding trade-offs between deep learning and classical approaches.

Manager for AI Networking Performance Research and Analysis at NVIDIA, focusing on optimizing networking technologies (NIC, Switch) for AI workloads like LLM training and inference. The role involves end-to-end performance strategy, from pre-silicon modeling to GA, and building telemetry frameworks and dashboards for performance tracking and root cause analysis. Requires strong experience in high-performance networking, cluster performance, and managing engineering teams, with a focus on Python, Bash, and C/C++.

Software engineer to design and develop C++ libraries and tools for unstructured sparsity in Deep Learning (DL) and High-Performance Computing (HPC) on NVIDIA GPUs. This involves DSL specifications, on-demand code generation, and enabling the system in Python/PyTorch. The role focuses on performance evaluation, library quality, and collaboration with product management.

Senior Software Engineer focused on performance optimizations for JAX, a deep learning framework, to build a scalable platform for data, training, and analysis. The role involves developing core JAX components, working with AI researchers, and building tools to improve AI system development efficiency.

Senior AI and FSI Developer Technology Engineer at NVIDIA focused on optimizing AI and HPC workloads on NVIDIA CPUs and GPUs for the financial services industry. The role involves researching, designing, and developing techniques to accelerate these workloads, profiling and eliminating performance bottlenecks, and collaborating with internal and external experts to influence future hardware and software designs. The engineer will also publish and present their work.

NVIDIA is looking for a Principal Developer Relations Manager for Financial Services to lead strategic engagement with developers and software providers to accelerate the adoption of NVIDIA's AI and computing platforms. The role involves acting as a technical advisor, integrating NVIDIA's software stack into partner products, guiding partners through onboarding, analyzing the developer ecosystem, and collaborating with internal teams and partners to drive AI adoption in financial services.

NVIDIA is seeking a Senior Architecture Energy Modeling Engineer to develop and deploy methodologies for energy-efficient products, focusing on building Machine Learning based power models for GPUs, CPUs, and Tegra SOCs. The role involves collaborating with various engineering teams to analyze and reduce power consumption, improve model accuracy, and integrate power models into simulation platforms.

Senior Software Engineer for NVIDIA's Autonomous Vehicles team, focusing on building groundbreaking technology at the intersection of automotive and robotics for parking and driving features. The role involves designing and implementing planning algorithms in C++ and supporting deployment on test vehicles.

Lead Safety Architect for NVIDIA's autonomous vehicle technology, focusing on integrating safety measures into DRIVE products and ensuring safety at scale. This role involves defining safety architecture, requirements, and metrics, and improving processes for safety analysis and data-driven evaluation.

This role focuses on improving the evaluation framework for autonomous vehicles, specifically for metric evaluation of vehicle-level behavior at scale. It involves enhancing the analytics framework and data pipeline, leveraging cloud platforms for large-scale metric evaluation and testing, and analyzing driving logs for behavior analysis and statistical analysis.

Principal Validation Analyst Engineer for Autonomous Vehicles at NVIDIA. This role focuses on developing and owning the system architecture for AV evaluation and validation, including data ingestion, metric calculation, and reporting. The engineer will establish technical standards, lead cross-team efforts, and architect scalable cloud and GPU-accelerated compute strategies for large-scale metric evaluation. The role also involves mentoring engineers and representing NVIDIA's validation approach externally.

Senior Solutions Architect for AI Compute at NVIDIA, focusing on deploying, managing, and validating AI Compute/HPC infrastructure for enterprise customers and partners. Requires strong Linux system administration, scripting, and cluster management skills, with experience in benchmarking tools and Kubernetes.

This role focuses on deploying, managing, and validating AI Compute/HPC infrastructure in Linux environments for NVIDIA's customers. It involves system design, networking, automation, and customer interaction to support large-scale AI projects. The role requires strong Linux system administration, scripting, and experience with cluster management and benchmarking tools like MLPerf.

Solutions Architect role focused on helping OEM customers build enterprise AI solutions using NVIDIA's AI technology, specifically focusing on the networking and storage demands for Generative AI, LLMs, and Deep Learning. The role involves architecting storage solutions, training partners, and acting as a technical authority on NVIDIA products, with an emphasis on high-performance storage systems and large-scale cluster bring-up.

Senior Solutions Architect at NVIDIA focused on helping large customers build and optimize AI/ML and HPC software solutions, particularly involving LLM training and inference on NVIDIA's hardware and software stack. The role involves deep technical engagement with customers, performance analysis, and solution development.

This role focuses on supporting NVIDIA's AI factory deployments by assisting with the deployment, debugging, and optimization of AI workloads on NVIDIA platforms. The Senior HPC Solutions Architect will work with customers to identify and resolve cluster performance and stability issues, benchmark framework features, and guide customers in scaling workloads on NVIDIA GPUs. The role requires strong networking and system-level understanding, with experience in large-scale training workloads and parallel applications.

NVIDIA is seeking an Autonomous Agent Engineer to build the infrastructure for secure and autonomous AI agent execution. This role involves designing and shipping SDKs, CLIs, and developer tooling for sandboxed compute environments, state management, and security boundaries for AI agents. The position requires strong systems engineering skills, experience with distributed systems and developer platforms, and proficiency in languages like Python or Go. Experience with agentic AI systems, sandboxing technologies, and security fundamentals is highly desirable.

Senior Software Engineer role focused on building the code generation backend for NVIDIA's deep learning compilers, connecting ML frontends to GPU compilation for high-performance kernel generation.

Senior Software Engineer role focused on container and cloud infrastructure for NVIDIA Inference Microservices (NIMs) and hosted services. The role involves designing and implementing container strategies, building enterprise-grade software for container build, packaging, and deployment, and improving reliability, performance, and scale across thousands of GPUs, with a focus on disaggregated LLM inference.

NVIDIA is seeking a Developer Technology Engineer to research, develop, and optimize deep learning, machine learning, and HPC workloads on NVIDIA's accelerated computing platform. The role involves working with customers and internal teams to address real-world use cases and performance challenges.

Senior Manager, Software Engineering at NVIDIA to lead the development of next-generation AI-driven solutions on the ServiceNow platform, focusing on enterprise integrations and agentic AI paradigms like RAG.

Senior Solutions Architect role focused on engaging with customers and partners to develop and support applications and platforms leveraging NVIDIA technology, particularly in HPC, Machine Learning, AI Physics, Foundation Modeling, Physical AI, and Agentic AI. Requires a strong technical background, customer-facing experience, and knowledge of modern AI architectures.

Senior Manager to lead the design, scaling, and operations of high-performance networking for GPU-based cloud infrastructure, critical for cloud gaming, AI/ML training, and inference platforms.

NVIDIA is seeking a Solution Architect to drive the adoption of their AI and accelerated computing libraries across industries. The role involves understanding customer workloads, designing solutions using NVIDIA libraries for LLM inference and training acceleration, and collaborating with product teams to improve features and performance. The candidate will also build technical assets and analyze industry trends.

Senior Software Engineer focused on integrating Agentic AI and ML into the software development lifecycle to create an intelligent ecosystem for developers, predicting failures, automating triage, and improving feedback loops. This involves building predictive models, AI agents for build/test selection, and LLM-based solutions for workflow automation.

Senior engineer to join NVIDIA's Math Libraries team, focusing on kernel generation for AI and HPC, specifically matrix operations, JITing, and fusions. The role involves designing and implementing high-performance numerical dense linear algebra software on GPUs, providing technical leadership, and collaborating with product management.

Seeking an engineering leader to productize neural simulation technologies (AlpaDreams, AlpaSim) for AV and robotics. This role involves building and scaling a team, hardening research into a production-quality platform, and establishing an open-source standard. Requires strong technical depth in ML, distributed systems, and production infrastructure, with a proven track record of shipping research-stage systems as scalable products.

NVIDIA is seeking an Architecture Energy Modeling Engineer to develop and deploy energy-efficient methodologies for their GPUs. This role involves building Machine Learning based power models, integrating them into simulators, and analyzing energy consumption of AI workloads to influence architectural improvements.

Senior Software Engineer to own and evolve the core NIM Platform SDK and microservice framework, powering NVIDIA Inferencing Microservices (NIM). Focus on high-performance systems programming, multi-cloud abstractions, and API framework development for production-ready AI inference at scale.

NVIDIA is seeking a Senior Cloud Infrastructure and DevOps Solutions Architect to manage and optimize large-scale AI/HPC infrastructure, focusing on Kubernetes, automation, monitoring, and customer engagement for AI operational projects.

NVIDIA is seeking a Solutions Architect with expertise in AI and data center infrastructure for the financial services sector. The role involves designing and deploying AI solutions, optimizing data center architectures, and collaborating with customers and internal teams to address complex technical challenges. Requires strong experience in accelerated computing, pre-sales, and large-scale systems management.

Senior Software Engineer to integrate NVIDIA Grove project into AI frameworks like Dynamo, Ray, and PyTorch, focusing on production-grade software for adoption, scaling, and operation. Responsibilities include building adapters, optimizing performance for distributed training/inference, and improving observability.

Senior Networking Solution Test Engineer at NVIDIA focusing on Ethernet-based AI clusters. Responsibilities include designing test requirements, building testbeds, owning end-to-end cluster troubleshooting, debugging networking components (NCCL, RoCE/RDMA), defining tests for automation, running regression/performance/functional/scale testing, and profiling deep learning workloads. Requires 5+ years of Linux networking/system-level testing, strong debugging skills, expertise in NIC validation, and knowledge of AI networking libraries and protocols.

This role focuses on inventing and pioneering AI-driven hardware development methodologies for ASICs, aiming to improve predictability, convergence, and turnaround time in the ASIC development lifecycle. The engineer will leverage data to enable AI models and analytics, establish metrics for improvement, share best practices, and track advances in AI, EDA, and hardware design research.

NVIDIA is seeking a Senior Technical Program Manager to drive robotics initiatives, focusing on foundation models, simulation-to-real workflows, and edge deployment. The role involves owning program execution across research, engineering, and product teams to ship robotics solutions at scale, requiring hands-on robotics experience and strong TPM skills.

NVIDIA is seeking a Senior Solutions Architect with expertise in GPU server platforms and AI infrastructure to help customers design, deploy, and optimize NVIDIA-based AI factories. The role involves leading presales and architecture engagements, designing end-to-end AI data center solutions, and supporting the deployment of NVIDIA platforms for LLM training and inference workloads.

Solution Architect role focused on designing AI computing platform architectures and supporting top AI Labs and model builders in integrating NVIDIA technologies for Deep Learning, HPC, Robotics, and Signal Processing applications. Requires experience with ML, data analytics, computer vision, and parallel programming on cloud/HPC architectures.

Senior Systems Performance Engineer at NVIDIA focused on validating and optimizing GPU accelerated computing products, specifically for Deep Learning/AI applications. The role involves system architecture, performance modeling, and developing stress/performance testing strategies for ML/LLM workloads.

Manager for a solution engineering team focused on customer support of NVIDIA software products (AI Enterprise, Omniverse, vGPU). The team will use AI to triage customer issues, identify solutions, and improve processes. Requires leadership, problem-solving, and AI/ML expertise.

Technical Program Manager to drive and deliver Enterprise software releases, focusing on Generative AI innovations, LLMs, and ML. The role involves managing technical alignment with partners, driving release planning with engineering and product teams, setting quality standards, and ensuring successful software product delivery. Requires strong program management experience, deep understanding of AI/ML frameworks, and ability to lead cross-functional teams.

Senior Technical Program Manager to lead end-to-end development of autonomous driving features, managing software development execution across multiple engineering teams for NVIDIA's autonomous vehicle platform.

This role focuses on inventing and pioneering AI-driven and sophisticated automation techniques to transform the way ASICs are conceived, explored, and brought to closure, improving predictability, convergence, and turnaround time in the ASIC development lifecycle. The role involves identifying and leveraging data for AI models, establishing metrics, sharing best practices, and tracking advances in AI and hardware design research.

Senior Developer Relations Manager for NVIDIA's Retail team, focusing on digital commerce. The role involves engaging with AI-native startups and software partners to help them build, optimize, and scale agentic AI solutions on NVIDIA platforms, including Nemotron models and Nemo Microservices. Responsibilities include acting as a technical point of contact, building sample applications, gathering developer feedback to influence product roadmap, and supporting startup integration and go-to-market strategies.

Senior Localization Engineer for Autonomous Vehicles at NVIDIA, focusing on building robust map-enhanced autonomous driving solutions with ASIL safety requirements. The role involves localizing to map data for precise environmental modeling, ensuring algorithms perform across diverse data and conditions, and writing efficient C++ code using CUDA for GPGPU programming, with a focus on productizing software for automotive standards.

This role focuses on architecting and optimizing NVIDIA's GPU Networking offerings for AI workloads, including distributed AI, deep learning, inference, and model serving. It involves co-designing hardware features and leading the architecture and development of new technologies and runtime systems for AI data centers.

Senior Software Engineer at NVIDIA focused on developing and productizing multi-sensor fusion algorithms for obstacle perception in autonomous driving solutions. The role involves designing, developing, and improving tracking and fusion algorithms to enhance the accuracy, robustness, and efficiency of detecting dynamic obstacles, with a strong emphasis on meeting product requirements for safety and latency.

Senior Dev Platform Engineer to build infrastructure for AI-assisted software development, focusing on workflow automation, multi-agent collaboration, AI-powered reviews, and enterprise tool integration.

NVIDIA is seeking a Senior Software Engineer for their Autonomous Vehicles Mapping team. The role involves designing and developing algorithms for map-based driving products, architecture design, and implementing efficient in-vehicle code. Key responsibilities include researching and developing transformer models for graphs, implementing evaluation frameworks for LLMs, fine-tuning pretrained models, building automated map content analysis, and creating scalable map-building workflows. The role requires a background in computer vision, 3D geometry, machine learning, and heavy AI tool usage for development.

This role focuses on architecting and scaling internal AI solutions for NVIDIA's cloud infrastructure, managing tools for AI development, identifying performance bottlenecks, and guiding engineers in solving complex AI-related problems. The role involves a mix of building AI agentic workflows and optimizing the underlying inference infrastructure.

NVIDIA is seeking an EDA Software R&D Engineer to develop internal EDA tools by fusing advances in parallel computing, machine learning, and novel algorithms in C++. The role involves inventing and developing new algorithms for RTL synthesis, digital logic optimization, and physical-aware synthesis techniques, with a focus on prototyping and evaluating ML methods to guide optimization decisions and integrating successful approaches into production.

Product Manager for Open Models at NVIDIA, focusing on community models like Nemotron, Llama, Gemma, DeepSeek, and Qwen. The role involves collaborating with model builders, tracking trends, supporting product marketing, enabling support for open models across inference, fine-tuning, and evaluation, and facilitating feedback loops. Requires 7+ years of product management experience, knowledge of the community model ecosystem, and comfort with Python code.

Senior Solution Architect, AI Compute Engineer at NVIDIA, focusing on deploying, managing, and maintaining AI/HPC infrastructure in Linux environments for customers. The role involves customer interaction, system design, automation, and providing feedback to internal teams. Requires strong Linux system administration, scripting, and cluster management skills, with a preference for experience in distributed computing, high-speed networking, automation tools, and Kubernetes for AI/ML workloads.

NVIDIA is seeking a Senior Robotics DevTech Engineer in China to act as a technical bridge between the robotics community and the global NVIDIA Omniverse platform team. The role involves supporting local robotics partners, building expertise in Isaac workflows, enabling partner iteration, and contributing to the product roadmap through market intelligence. Responsibilities include local ecosystem triage and support, developing expertise in robotics simulation tools, translating partner needs to engineering, and generating regional insights.

This role focuses on assisting customers in adopting NVIDIA's GPU hardware and software for building and deploying AI/ML and data analytics solutions on cloud platforms. The Solutions Architect acts as a technical expert, engaging with developers, researchers, and data scientists, and partnering with sales teams to drive end-to-end technology solutions.

Software Engineer role focused on building and maintaining CI/CD pipelines, automation, and performance optimization for a large-scale robotics simulation and learning platform (Isaac Lab). The role involves infrastructure for ML and simulation systems, benchmarking, profiling, and supporting issue triage.

Software Engineer for NVIDIA's Isaac Lab team, focusing on developing and extending physics simulation APIs for robot learning. The role involves debugging simulation issues, translating research into APIs, and engaging with the robotics community. Requires extensive Python and deep learning stack experience, with a strong background in physics simulation or robotics control, and experience in reinforcement learning and imitation learning.

NVIDIA is seeking a Devtech Compute Engineer to develop performance-critical code for deep learning applications, focusing on accelerating model training and inference on GPUs, particularly for recommender systems. The role involves optimizing CUDA kernels, integrating solutions into open-source libraries, and collaborating with hardware teams to define future solutions across various domains like LLM, Recsys, Robotics, and Assisted Driving.

This role focuses on architecting and enhancing NVIDIA's GPU Networking offerings to accelerate AI workloads, including distributed AI, deep learning, inference, and model serving. It involves co-designing hardware features and leading the architecture and design of new technologies for AI data centers.

NVIDIA is seeking a Solutions Architect Intern focused on Robotics to support local partners and customers in Japan. The intern will work on setting up data augmentation pipelines and analyzing synthetic data's impact on VLA performance and generalizability, using tools like Isaac Sim and Cosmos.

Senior Networking Solution Test Engineer focused on debugging large-scale AI clusters, NVLink, Ethernet, and InfiniBand. The role involves designing tests, building testbeds, end-to-end troubleshooting, collaborating with development teams on networking components, and profiling deep learning workloads.

This role focuses on optimizing GPU-accelerated code for training and inference performance of large-scale recommender systems. It involves designing and implementing high-performance C++/CUDA components, developing tests, and optimizing data flows between GPUs, NICs, and SSDs. The ideal candidate has experience with C++, CUDA, Python, GPU performance profiling, and ideally, building or optimizing recommender systems or production ML workloads on GPUs.

NVIDIA is seeking a Senior Compiler Engineer for its Deep Learning Compiler (DLC) team. This role involves analyzing deep learning networks, developing compiler optimization algorithms, and collaborating with framework and hardware teams to accelerate deep learning inference. The compiler is critical for delivering leading inference performance, fast build times, and reduced memory footprints across various platforms.

Senior AI Developer Technology Engineer focused on optimizing AI and HPC workloads for financial markets on NVIDIA's computing platforms. This role involves research, development, performance analysis, and collaboration with the developer community and internal teams to influence hardware and software design.

Solutions Architect role focused on helping customers adopt NVIDIA's GPU hardware and software for building and deploying AI/ML and data analytics solutions on cloud platforms. Involves customer engagement, technical content delivery, and PoC development.

Senior Solutions Architect focused on deploying, debugging, and optimizing large-scale AI training and inference workloads on GPU clusters. The role involves collaborating with internal teams and external customers to solve complex HPC and AI challenges, focusing on performance, stability, and scaling of AI workloads.

Senior Application Engineer role focused on accelerating materials and chemical discovery using AI, involving collaboration with developers and researchers on building, fine-tuning, and optimizing AI models and agentic workflows. The role requires experience with AI frameworks, benchmarking domain-specific models, and communicating technical value.

NVIDIA is seeking a Neural Graphics Engineer to work on technologies at the intersection of AI and real-time rendering. The role involves implementing and optimizing neural graphics techniques, prototyping neural rendering and generative 3D approaches, and contributing to the graphics software stack. Experience with C++, Python, computer graphics, and machine learning is required, with a preference for hands-on experience in neural rendering or generative AI for 3D content.

NVIDIA is seeking a Senior Technical Product Manager to define and build the future of their self-driving software, focusing on planning and controls for autonomous vehicles. The role involves understanding technical aspects of classical and AI planners, identifying problems, designing solutions, prioritizing roadmaps, and collaborating with engineering teams to deliver advanced planning and controls technology for L4 robotaxis.

This role focuses on inventing and pioneering AI-driven automation techniques to transform ASIC development methodology, improving predictability, convergence, and turnaround time. The engineer will identify bottlenecks, curate data for AI models, establish metrics, share best practices, and track advances in AI and hardware design research.

NVIDIA is seeking an AI Benchmarking and Telemetry Engineer to develop and execute benchmarking approaches for large-scale HPC and AI clusters, and build telemetry frameworks to capture system performance data from host level through network and data center infrastructure. The role involves collaborating with engineering teams, customers, and partners to ensure platform performance and reliability, and maintaining knowledge of industry-standard benchmarks.

Senior System Software Engineer focused on integrating and deploying AI models (foundation models, embodied AI, RL policies) into humanoid robot systems, optimizing system performance, and developing validation workflows. This role involves working with robotics, systems, AI, and simulation experts to enable real-world deployment of embodied AI.

This role focuses on architecting and optimizing cloud infrastructure for AI workloads, specifically for the GeForce NOW service. The engineer will perform deep performance and power analysis of GPU/CPU microarchitecture for AI inference, deploy and optimize AI/gaming kernels, and build models to guide platform decisions balancing performance, power, and cost. The role requires strong programming skills and experience with AI models and performance analysis methodologies.

NVIDIA is seeking an experienced Senior Site Reliability Engineer to scale its AI Infrastructure, focusing on production systems for large GPU clusters used in AI workloads. The role involves implementing monitoring, health management, and automation for GPU asset provisioning, configuration, and lifecycle management across cloud providers, ensuring reliability, availability, and scalability. The engineer will collaborate with teams to maintain reliable and performant AI clusters, evaluate system failures, and improve services.

Senior AI Applications Engineer for NVIDIA's Finance team, focusing on building and scaling AI-powered interfaces and applications for non-technical finance employees. The role involves end-to-end delivery, integrating AI tools, securing services, and translating prototypes into production-ready software.

NVIDIA is seeking an HPC and AI Cluster Engineer to manage and maintain large-scale HPC/AI clusters, including Linux job scheduling, CI/CD pipelines, and troubleshooting from bare metal to application level. The role involves supporting R&D activities and POCs, working with cutting-edge hardware and software, and collaborating with researchers and customers to develop solutions.

NVIDIA is seeking a GPU Computing Engineer in Shanghai to analyze Deep Learning models and investigate TensorRT stability and performance issues. The role involves working with a global team on CUDA and TensorRT development, extracting feature requirements, and generating documentation. Requires strong C/C++/Python skills, knowledge of inference networks, and experience with deep learning frameworks like PyTorch.

Senior Software Engineer to lead the development of AI software resiliency for large-scale AI supercomputers (100,000+ GPUs), focusing on features like fast checkpoint-recovery, error detection/isolation, and straggler/hang detection to minimize cluster downtime. The role involves hands-on C++ and Python coding, optimization for AI workloads, fault tolerance, debugging, and collaboration with AI researchers and hardware/software teams to integrate resiliency into AI frameworks.

Senior Software Engineer role focused on shaping application architecture for autonomous vehicles, integrating and adapting NVIDIA solutions, and refining planning and control systems. Requires strong background in control theory, motion planning, deep learning, and C++/Python development.

Senior Software Engineer to build and improve AI Assisted Developer Tools connected through web APIs, IDEs and agents. Architect cloud solutions leveraging Nvidia microservices and frameworks, integrating deeply with developer workflows to accelerate the full product lifecycle.

Lead engineer responsible for defining strategy and architecting/building the MLOps platform for NVIDIA's healthcare data programs, ensuring data quality, governance, and serving for model training and evaluation.

Software Engineer role focused on building a distributed systems platform for autonomous AI agents, including secure sandboxed runtimes, inference routing, and policy enforcement. The role involves full-stack development, network security, and operability.

NVIDIA is seeking a Senior Manager for their Autonomous Vehicles team to lead and grow a team responsible for planning and controls software, from L2 to L4 driving. The role involves hands-on leadership, driving delivery of technology portfolios, and collaborating with internal and external partners to achieve ambitious roadmaps. Requires strong technical skills in robotics motion planning/controls and experience managing technical teams in the AV/robotics domain.

Solution Architect role at NVIDIA, focusing on supporting government clients in adopting AI solutions. The role involves technical consulting, developing AI-enabled plans, assisting with proofs of concept, productization, and advising on delivery. Requires experience in Computer Vision, Deep Learning, or Generative AI, with specific experience in fine-tuning or deploying models and deploying agentic/Gen AI solutions. Hands-on experience with Python, PyTorch, and containers is necessary.

Distinguished Engineer to anchor the Foundation Model (FM) Hosting team, focusing on efficient, reliable, and rapid serving of large language models at scale. The role involves pushing the limits of LLM inference, owning the technical strategy for the FM serving stack, and bridging the gap between AI Science and production infrastructure. Responsibilities include designing and driving the roadmap for high throughput, ultra-low latency, and optimal GPU utilization, leading performance engineering, and co-designing model architectures for deployability with AI Research & Science teams.

This role focuses on research and development of GenAI powered conversational capabilities and scalable futuristic solutions for customer digital experience and real-time support. The primary focus is on fine-tuning LLMs for domain-specific conversational applications, inference optimization, and multi-agentic workflows, with a secondary focus on building these agentic systems.

Senior Distinguished AI Engineer focused on building and scaling an Agentic AI Platform at Capital One. The role involves contributing to platform architecture, standardizing agentic workflows using frameworks like LangGraph and AutoGen, developing GenAI SDKs/CLIs, implementing central guardrail services for trust and safety, optimizing orchestration for cost reduction, and driving innovation in areas like multimodal RAG and hierarchical agent memory. The role also includes coaching and evangelizing the platform vision.

Applied Researcher II focused on AI Foundations, LLM Core, and Agentic AI at Capital One. The role involves partnering with cross-functional teams to deliver AI-powered products, leveraging technologies like PyTorch and VectorDBs. Responsibilities include building AI foundation models through all development phases (design, training, evaluation, validation, implementation) and conducting high-impact applied research to advance customer experiences. The ideal candidate has a deep understanding of AI methodologies, experience building large deep learning models (language, images, events, graphs), expertise in training optimization, self-supervised learning, robustness, explainability, or RLHF, and a track record of delivering models at scale. A PhD or MS with significant experience is required, with a focus on NLP, geometric deep learning, or optimization.

Applied Researcher I role focused on AI Foundations, LLM Customization, Finetuning, and Reinforcement Learning within Capital One's fintech domain. The role involves partnering with cross-functional teams to deliver AI-powered products, building AI foundation models through all development phases, and conducting applied research to enhance customer experiences. Requires a strong technical background in deep learning, model training, and experience with open-source tools and cloud platforms.

Applied Researcher role focused on AI Foundations, LLM Customization, Finetuning, and Reinforcement Learning within a fintech company. The role involves partnering with cross-functional teams to deliver AI-powered products, leveraging technologies like Pytorch and VectorDBs, and building AI foundation models through all development phases. It emphasizes applied research to improve customer experiences and requires a deep understanding of AI methodologies, experience building large deep learning models, and a track record of delivering models at scale.

Applied Researcher II role focused on building AI foundation models through all phases of development, from design through training, evaluation, validation, and implementation. The role involves high-impact applied research to push the latest AI developments into customer experiences, leveraging technologies like Pytorch, AWS, Huggingface, and VectorDBs. Requires a PhD or MS with significant experience in AI/ML, with expertise in areas like training optimization, self-supervised learning, robustness, explainability, or RLHF, and a track record of delivering models at scale.

Senior Director of Applied Research leading teams to drive strategic direction in AI at Capital One, focusing on building AI foundation models from design through training, evaluation, validation, and implementation, and engaging in high-impact applied research to create next-generation customer experiences. The role involves people management, external representation in the research community, and leveraging a broad stack of technologies for AI-powered products in fintech.

Applied Researcher role focused on AI Foundations, LLM Customization, Finetuning, and Reinforcement Learning within a fintech company. The role involves partnering with cross-functional teams to deliver AI-powered products, leveraging technologies like Pytorch and VectorDBs, and building AI foundation models through all development phases. It emphasizes applied research to improve customer experiences and requires a deep understanding of AI methodologies, experience building large deep learning models, and a track record of delivering models at scale.

Applied Researcher role focused on AI Foundations, LLM Customization, Finetuning, and Reinforcement Learning within a fintech company. The role involves partnering with cross-functional teams to deliver AI-powered products, leveraging technologies like Pytorch and VectorDBs, and building AI foundation models through all development phases. It emphasizes applied research to improve customer experiences and requires a deep understanding of AI methodologies, experience building large deep learning models, and a track record of delivering models at scale.

Applied Researcher I focused on AI Foundations, LLM Core, and Agentic AI at Capital One. The role involves partnering with cross-functional teams to deliver AI-powered products, leveraging technologies like PyTorch, AWS, Huggingface, and VectorDBs. Responsibilities include building AI foundation models through all development phases (design, training, evaluation, validation, implementation) and conducting applied research to create next-generation customer experiences. Requires a PhD or MS with experience in AI/ML, with a strong understanding of AI methodologies, experience building large deep learning models (language, images, events, graphs), and expertise in optimization, self-supervised learning, robustness, explainability, or RLHF. An engineering mindset with a track record of delivering models at scale and experience in delivering libraries or platform code is essential. A track record of high-quality ideas or improvements demonstrated by publications or projects is also required.

Applied Researcher II (AI Foundations) at Capital One, focusing on building AI foundation models from design through training, evaluation, validation, and implementation. The role involves applied research to develop next-generation customer experiences and requires experience with large deep learning models, training optimization, and delivering models at scale. The position is research-oriented within the fintech domain.

Applied Researcher I role focused on building AI foundation models, engaging in applied research to improve customer experiences, and delivering AI-powered products. The role involves training optimization, self-supervised learning, robustness, explainability, and RLHF, with an emphasis on delivering models at scale.

Applied Researcher II focused on AI Foundations at Capital One, working on building AI foundation models from design through training, evaluation, validation, and implementation. The role involves applied research to integrate AI developments into customer experiences and requires experience with large deep learning models, training optimization, and delivering models at scale. Collaboration with cross-functional teams and a strong understanding of AI methodologies are key.

Applied Researcher I (AI Foundations) at Capital One, focusing on building AI foundation models from design through training, evaluation, validation, and implementation. The role involves applied research to push AI developments into customer experiences, leveraging technologies like Pytorch, AWS, Huggingface, and VectorDBs. Requires a PhD or MS with experience in AI/ML, deep learning, and delivering models at scale, with a strong understanding of AI methodologies and experience in training optimization, self-supervised learning, robustness, explainability, or RLHF.

Distinguished Applied Researcher role focused on building AI foundation models from design through training, evaluation, validation, and implementation, and engaging in high-impact applied research to develop next-generation customer experiences. The role involves partnering with cross-functional teams and leveraging technologies like PyTorch, AWS, Huggingface, and VectorDBs. Requires a PhD or MS with significant experience in applied research, with a focus on large deep learning models, training optimization, self-supervised learning, robustness, explainability, or RLHF. Experience training large language models from scratch or through continued pre-training is highly preferred.

This role is for an Applied Researcher II at Capital One focused on building AI foundation models and applying state-of-the-art AI to customer-facing products. The role involves research, development, training, evaluation, and implementation of AI models, with a strong emphasis on pushing AI capabilities into next-generation customer experiences. The candidate will work with cross-functional teams and leverage various technologies including Pytorch, AWS, Huggingface, and VectorDBs. Experience in training optimization, self-supervised learning, robustness, explainability, RLHF, and delivering models at scale is required. A PhD or MS in a related field with significant research experience is preferred, along with a publication record.

Applied Researcher I role focused on AI Foundations, LLM Core, and Agentic AI at Capital One. The role involves partnering with cross-functional teams to deliver AI-powered products, leveraging technologies like Pytorch and VectorDBs, and building AI foundation models through all development phases. It emphasizes applied research to advance customer experiences and requires a deep understanding of AI methodologies, experience building large deep learning models, and a track record of delivering models at scale.

Applied Researcher II at Capital One focused on AI Foundations, LLM Core, and Agentic AI. The role involves partnering with cross-functional teams to deliver AI-powered products, leveraging technologies like Pytorch and VectorDBs. Responsibilities include building AI foundation models through all development phases (design, training, evaluation, validation, implementation) and engaging in applied research to advance customer experiences. The ideal candidate has a deep understanding of AI methodologies, experience building large deep learning models (language, images, events, graphs), expertise in optimization, self-supervised learning, robustness, explainability, or RLHF, and a track record of delivering models at scale. Experience with LLMs, including pre-training and fine-tuning, is highly preferred.

Applied Researcher I (AI Foundations) at Capital One, focusing on building AI foundation models through all phases of development, from design through training, evaluation, validation, and implementation. The role involves applied research to push state-of-the-art AI into customer experiences, leveraging technologies like Pytorch, AWS, Huggingface, and VectorDBs. Requires a PhD or MS with experience in AI/ML, deep learning, and delivering models at scale.

Senior Manager, Data Scientist - Applied AI role at Capital One, focusing on building and shipping Gen AI models for the US Card business. The role involves partnering with cross-functional teams to deliver AI-powered products, leveraging technologies like Pytorch, AWS, Hugging Face, LangChain, and VectorDBs. Responsibilities include adapting and fine-tuning LLMs for customer-facing applications, building Gen AI and Sequence models through all development phases, and operationalizing them in production systems serving over 80 million customers. The ideal candidate is customer-focused, innovative, creative, a leader, technical with hands-on LLM experience, and influential. Experience in training language models, computer vision models, and subdomains like self-supervised learning, explainability, and RLHF is desired, along with an engineering mindset for delivering models at scale.

Sr. Distinguished Applied Researcher at Capital One focused on building AI foundation models through all phases of development, from design through training, evaluation, validation, and implementation. The role involves high-impact applied research to integrate the latest AI developments into customer experiences, leveraging technologies like Pytorch, AWS, Huggingface, and VectorDBs. This individual contributor role requires guiding and mentoring teams, representing Capital One in the research community, and delivering AI-powered products and platforms.

Distinguished AI Engineer responsible for designing, developing, testing, deploying, and supporting AI software components including foundation model training, LLM inference, similarity search, guardrails, model evaluation, experimentation, governance, and observability. The role involves optimizing performance, scalability, cost, and latency of large-scale production AI systems, and contributing to the technical vision and roadmap of foundational AI systems.

Lead Machine Learning Engineer focused on designing, building, and productionizing Generative AI applications and Agentic Workflow systems at scale. The role involves building robust ML serving architecture, developing high-performance code, and ensuring low latency and high availability of AI solutions, with a strong emphasis on cloud-native platforms and MLOps.

Senior Manager of Data Science focused on LLM customization within Capital One's AI Foundations team. The role involves partnering with cross-functional teams to deliver AI-powered products, leveraging technologies like PyTorch, Hugging Face, LangChain, and VectorDBs. Responsibilities include adapting and fine-tuning LLMs for business applications, building NLP models through development phases, and operationalizing them in production systems. The ideal candidate has experience in training language models, expertise in areas like self-supervised learning or RLHF, and a track record of delivering models at scale.

Lead AI/ML Engineer focused on building and optimizing AI platforms and infrastructure, including foundation model training, LLM inference, similarity search, guardrails, and evaluation. The role involves designing, developing, and deploying AI software components, leveraging various AI technologies, and improving the performance of large-scale production AI systems.

Distinguished AI Engineer role focused on designing, developing, and deploying AI software components including foundation model training, LLM inference, similarity search, guardrails, evaluation, and observability. The role involves optimizing performance, scalability, cost, and latency of large-scale production AI systems, leveraging cloud platforms and AI technologies. It requires a strong engineering and mathematics foundation, with experience in Python, Go, Scala, or Java, and cloud deployment.

Lead AI Engineer role focused on building and optimizing Gen AI Platform Services. Responsibilities include designing, developing, testing, deploying, and supporting AI software components such as foundation model training, LLM inference, similarity search, guardrails, model evaluation, experimentation, governance, and observability. The role involves leveraging various AI technologies and optimizing large-scale production AI systems for performance, scalability, cost, and latency.

Applied Researcher I role focused on building AI foundation models through all phases of development, from design through training, evaluation, validation, and implementation. The role involves high-impact applied research to push the latest AI developments into next-generation customer experiences, leveraging technologies like Pytorch, AWS Ultraclusters, Huggingface, Lightning, and VectorDBs. Experience with training optimization, self-supervised learning, robustness, explainability, and RLHF is desired, with a track record of delivering models at scale.

Manager of Data Science focused on AI Software Engineering, designing and building scalable AI architectures for the software development lifecycle using multi-agent solutions. The role involves partnering with cross-functional teams, leveraging technologies like Python, AWS, and Spark, and building ML models through all phases of development. Experience with agentic platforms, RAG, and advanced model customization is preferred.

Distinguished Engineer role focused on building agentic AI systems for real-time marketing and personalized sales within the enterprise banking domain. The role involves prototyping, defining technical strategy, and scaling these systems, with a focus on influencing architecture and evangelizing AI adoption.

Manager, Data Science role focused on GenAI for a digital assistant, involving research, development, fine-tuning LLMs, inference optimization, and multi-agentic workflows. Leverages Python, AWS, LangChain, LangGraph, HuggingFace, vLLM, and VectorDBs. Aims to improve customer experience through intelligent digital assistance.

Capital One is seeking a Principal Associate Data Scientist to join their LLM Customization Team. This role involves partnering with cross-functional teams to deliver AI-powered products, leveraging technologies like Pytorch, Hugging Face, LangChain, and VectorDBs. The primary focus is on adapting and fine-tuning LLMs for business-specific applications, building NLP models through all phases of development, and operationalizing them in production systems.

Manager, Data Scientist role focused on building and deploying personalized recommendation engines using Foundation Models and Reinforcement Learning. The role involves partnering with cross-functional teams, leveraging technologies like Python and AWS, and building ML models through all phases of development. Expertise in Transformer-based architectures and scalable systems is required.

This role focuses on designing, developing, testing, deploying, and supporting AI software components for foundational AI systems at Capital One. Key responsibilities include foundation model training, LLM inference, similarity search, guardrails, model evaluation, governance, and observability. The role also involves optimizing LLM performance for scalability, cost, latency, and throughput, leveraging technologies like AWS, Huggingface, VectorDBs, and PyTorch. The goal is to build and deploy proprietary AI solutions that deliver value to millions of customers and enhance products with AI capabilities.

Lead AI Engineer focused on building and optimizing AI Foundations, including foundation model training, LLM inference, similarity search, guardrails, evaluation, governance, and observability. The role involves designing, developing, testing, deploying, and supporting AI software components, with a strong emphasis on improving performance (scalability, cost, latency, throughput) of large-scale production AI systems using state-of-the-art LLM optimization techniques. The role also touches on agentic systems through guardrails and similarity search, and model evaluation.

Senior Lead AI Engineer role focused on building and scaling Gen AI Platform Services, including foundation model training, LLM inference, similarity search, guardrails, and model evaluation. The role involves optimizing AI systems for performance, cost, and latency, and contributing to the technical vision for foundational AI systems at Capital One.

Applied Researcher II focused on AI Foundations, LLM Core, and Agentic AI at Capital One. The role involves partnering with cross-functional teams to deliver AI-powered products, leveraging technologies like Pytorch, AWS, Huggingface, and VectorDBs. Responsibilities include building AI foundation models through all development phases (design, training, evaluation, validation, implementation) and conducting high-impact applied research to improve customer experiences. The ideal candidate has a strong technical background, experience building large deep learning models, expertise in areas like training optimization, self-supervised learning, robustness, explainability, or RLHF, and a track record of delivering models at scale. Experience with LLM pre-training, optimization, or fine-tuning is highly preferred.

Applied Researcher I role focused on building AI foundation models and delivering AI-powered products, leveraging state-of-the-art AI developments for customer experiences. The role involves research, training, evaluation, and implementation of large deep learning models, with a focus on optimization, self-supervised learning, robustness, explainability, and RLHF.

Senior Lead AI Engineer responsible for designing, developing, testing, deploying, and supporting AI software components including foundation model training, LLM inference, similarity search, guardrails, model evaluation, experimentation, governance, and observability. The role involves optimizing LLM performance for scalability, cost, latency, and throughput, and contributing to the technical vision and roadmap of foundational AI systems. The role leverages various AI technologies and requires strong engineering and mathematical foundations.

Lead AI Engineer role focused on designing, developing, testing, deploying, and supporting AI software components including foundation model training, LLM inference, similarity search, guardrails, model evaluation, experimentation, governance, and observability. The role involves optimizing LLM performance for scalability, cost, latency, and throughput, and contributing to the technical vision and roadmap of foundational AI systems. It requires experience with AI/ML algorithms, programming languages like Python, and cloud platforms, with a focus on deploying scalable and responsible AI solutions.

This role focuses on designing, developing, testing, deploying, and supporting AI software components, including foundation model training, LLM inference, similarity search, guardrails, model evaluation, experimentation, governance, and observability. The engineer will invent and introduce LLM optimization techniques to improve the performance (scalability, cost, latency, throughput) of large-scale production AI systems, leveraging technologies like AWS Ultraclusters, Huggingface, VectorDBs, Nemo Guardrails, and PyTorch. The role involves contributing to the technical vision and roadmap of foundational AI systems.

Lead AI Engineer focused on AI Foundations, responsible for designing, developing, testing, deploying, and supporting AI software components including foundation model training, LLM inference, similarity search, guardrails, model evaluation, governance, and observability. The role involves optimizing large-scale production AI systems for performance (scalability, cost, latency, throughput) using various AI technologies and contributing to the technical vision and roadmap of foundational AI systems.

Senior Lead AI Engineer role focused on building and deploying AI-powered products and foundational AI systems at Capital One. Responsibilities include designing, developing, testing, deploying, and supporting AI software components like foundation model training, LLM inference, similarity search, guardrails, model evaluation, experimentation, governance, and observability. The role involves leveraging AI technologies and optimizing LLM performance for scalability, cost, and latency.

Senior Lead AI Engineer role focused on building and scaling Gen AI platform services, including foundation model training, LLM inference, similarity search, guardrails, and model evaluation. The role involves optimizing performance (scalability, cost, latency, throughput) of large-scale production AI systems and contributing to the technical vision for foundational AI systems. Requires strong engineering and AI expertise, with experience in cloud platforms and programming languages like Python.

Lead AI Engineer role focused on building and deploying AI-powered products and foundational AI systems, including LLM inference, similarity search, guardrails, and model evaluation, with an emphasis on optimizing performance and scalability for enterprise use.

Lead AI Engineer role focused on building and deploying AI-powered products and foundational AI systems at Capital One. The role involves designing, developing, testing, deploying, and supporting AI software components including foundation model training, LLM inference, similarity search, guardrails, model evaluation, experimentation, governance, and observability. It requires leveraging a broad stack of AI technologies and optimizing LLM performance for scalability, cost, and latency.

Senior Manager, AI Engineering (People Leader) for Gen AI Platform Services at Capital One. This role involves overseeing the design, development, testing, deployment, and support of AI software components, including foundation model training, LLM inference, similarity search, guardrails, model evaluation, experimentation, governance, and observability. The candidate will make build-vs-buy decisions, optimize LLM performance (scalability, cost, latency, throughput), contribute to the technical vision and roadmap of foundational AI systems, and lead/mentor an AI engineering team. Experience with cloud platforms and deploying scalable AI solutions is required.

Product Manager to execute technical AI vision, scale AI use cases, data infrastructure, development velocity, and knowledge governance. Design agentic workflows, evaluate LLM models, build agentic-first architectures, and connect AI to business goals.

This role focuses on architecting and launching conversational AI experiences for millions of customers, involving foundation model training, LLM inference, and optimization of AI systems. It requires partnering with cross-functional teams to deliver AI-powered products and leveraging a broad stack of AI technologies.

Senior Lead AI Engineer focused on LLM inference and hosting infrastructure, optimizing performance, scalability, cost, and latency for large-scale production AI systems. The role involves designing, developing, and deploying AI software components, including foundation model training, inference, similarity search, guardrails, evaluation, governance, and observability, leveraging various AI technologies and cloud platforms.

This role focuses on engineering AI foundations, including foundation model training, LLM inference, similarity search, guardrails, model evaluation, and optimization techniques for scalability, cost, latency, and throughput. It involves leveraging AI technologies and contributing to the technical vision and roadmap of foundational AI systems.

Lead AI Engineer focused on building and optimizing foundational AI systems, including LLM inference, similarity search, guardrails, and model evaluation, to enhance customer and associate experiences within a large enterprise.

Lead AI Engineer role focused on building and deploying AI-powered products, including foundation model training, LLM inference, similarity search, guardrails, and model evaluation. The role involves leveraging AI technologies like AWS Ultraclusters, Huggingface, VectorDBs, and Nemo Guardrails, and optimizing LLM performance for scalability, cost, and latency. The position requires a strong engineering foundation and experience in AI/ML algorithm development and deployment on cloud platforms.

Capital One is seeking a Director, Data Scientist to lead the Generative AI Systems team. This role involves building and operationalizing AI-powered products, specifically focusing on LLMs for customer-facing applications in dialogue, summarization, comprehension, speech, and image processing. The position requires leading a team of specialists, experimenting with generative AI, and contributing to research. The role emphasizes partnering with cross-functional teams, leveraging technologies like PyTorch, AWS, Hugging Face, LangChain, and VectorDBs, and managing the full ML lifecycle from design to production for over 80 million customers.

Lead AI Engineer role focused on building and deploying AI-powered products, including foundation model training, LLM inference, similarity search, guardrails, and model evaluation. The role involves leveraging AI technologies like AWS Ultraclusters, Huggingface, VectorDBs, and Nemo Guardrails, and optimizing LLM performance for scalability, cost, and latency. The position requires a strong engineering foundation and experience in AI/ML algorithm development and deployment on cloud platforms.

Applied Researcher II at Capital One focused on building AI foundation models through all phases of development, from design through training, evaluation, validation, and implementation. The role involves high-impact applied research to push AI developments into customer experiences, leveraging technologies like Pytorch, AWS, Huggingface, and VectorDBs. Requires experience building large deep learning models and delivering models at scale.

Applied Researcher I at Capital One focused on building AI foundation models and delivering them at scale for customer-facing products. The role involves partnering with cross-functional teams, leveraging various technologies, and conducting applied research to push AI capabilities into next-generation customer experiences. Requires a strong technical background in deep learning, model training, optimization, and a track record of delivering models in production.

Lead AI Engineer role focused on designing, developing, testing, deploying, and supporting AI software components including foundation model training, LLM inference, similarity search, guardrails, model evaluation, experimentation, governance, and observability. The role involves leveraging AI technologies, inventing LLM optimization techniques to improve performance (scalability, cost, latency, throughput) of large-scale production AI systems, and contributing to the technical vision and roadmap of foundational AI systems. Requires strong engineering and mathematics foundation, expertise in hardware, software, and AI, and experience with cloud platforms and AI/ML algorithms.

Senior Lead AI Engineer role focused on building and deploying AI-powered products and foundational AI systems within an enterprise setting. Responsibilities include designing, developing, testing, deploying, and supporting AI software components such as foundation model training, LLM inference, similarity search, guardrails, model evaluation, and observability. The role emphasizes optimizing LLM performance for scalability, cost, latency, and throughput, and contributing to the technical vision and roadmap of foundational AI systems.

Lead AI Engineer role focused on designing, developing, testing, deploying, and supporting AI software components including foundation model training, LLM inference, similarity search, guardrails, model evaluation, experimentation, governance, and observability. The role involves leveraging AI technologies and optimizing LLM performance for scalability, cost, latency, and throughput in production AI systems within an enterprise setting.

Senior Lead AI Engineer role focused on building and deploying AI-powered products and foundational AI systems, including LLM inference, optimization, and agentic AI platforms. The role involves designing, developing, testing, deploying, and supporting AI software components, leveraging various AI technologies, and contributing to the technical vision and roadmap.

This role focuses on engineering AI-powered products and platforms, specifically within Generative AI. Responsibilities include designing, developing, and supporting AI software components like foundation model training, LLM inference, similarity search, guardrails, model evaluation, experimentation, governance, and observability. The role also involves optimizing LLM performance for scalability, cost, latency, and throughput, leveraging various AI technologies and cloud platforms.

This role focuses on building and scaling the intelligence and infrastructure for real-time, personalized customer experiences using ML and GenAI systems. It involves defining technical strategy, partnering with data science and ML platform teams, developing a rules engine, building ML infrastructure for end-to-end workflows, architecting low-latency event-driven systems, driving MLOps, and optimizing LLM performance for production AI systems. The role also involves providing technical leadership and leveraging various AI technologies.

Lead AI Engineer role focused on building and scaling Gen AI platforms, agentic AI systems, and LLM infrastructure. The role involves designing, developing, and deploying AI software components including foundation model training, LLM inference, similarity search, guardrails, model evaluation, and observability. It emphasizes optimizing LLM performance for scalability, cost, latency, and throughput, and leveraging a broad stack of AI technologies.

Lead AI Engineer role focused on building and deploying AI-powered products and foundational AI systems within a fintech company. Responsibilities include designing, developing, testing, deploying, and supporting AI software components such as foundation model training, LLM inference, similarity search, guardrails, model evaluation, and observability. The role emphasizes optimizing LLM performance (scalability, cost, latency, throughput) and contributing to the technical vision and roadmap for AI systems. Requires experience with AI/ML algorithms, programming languages like Python, and cloud platforms, with a focus on deploying scalable and responsible AI solutions.

This role focuses on engineering and deploying AI-powered products and foundational AI systems, including large language model inference, optimization, and related components like similarity search and guardrails. The primary focus is on the serving and optimization of AI models in production, with a secondary involvement in agentic systems.

Senior Lead AI Engineer role focused on designing, developing, testing, deploying, and supporting AI software components including foundation model training, LLM inference, similarity search, guardrails, model evaluation, experimentation, governance, and observability. The role involves inventing and introducing state-of-the-art LLM optimization techniques to improve the performance of large-scale production AI systems, leveraging technologies like AWS Ultraclusters, Huggingface, VectorDBs, and Nemo Guardrails. This position is key to bringing AI capabilities to life at Capital One, empowering teams across the company and delivering value to millions of customers.

Applied Researcher II focused on AI Foundations at Capital One. The role involves partnering with cross-functional teams to deliver AI-powered products, leveraging technologies like Pytorch and VectorDBs. Responsibilities include building AI foundation models through all development phases (design, training, evaluation, validation, implementation) and conducting applied research to integrate AI advancements into customer experiences. The ideal candidate has a deep understanding of AI methodologies, experience building large deep learning models, and a track record of delivering models at scale.

Applied Researcher I role focused on building AI foundation models through all phases of development, from design through training, evaluation, validation, and implementation. The role involves high-impact applied research to push the latest AI developments into customer experiences, leveraging technologies like Pytorch, AWS, Huggingface, and VectorDBs. Requires a PhD or MS with experience in AI/ML, with expertise in areas like training optimization, self-supervised learning, robustness, explainability, or RLHF, and a track record of delivering models at scale.

Lead AI Engineer focused on AI Foundations, LLM Customization and Finetuning within Capital One's Intelligent Foundations and Experiences (IFX) team. The role involves designing, developing, testing, deploying, and supporting AI software components including foundation model training, LLM inference, similarity search, guardrails, model evaluation, experimentation, governance, and observability. It also emphasizes optimizing LLM performance for scalability, cost, and latency in production AI systems.

Applied Researcher II focused on AI Foundations at Capital One. The role involves partnering with cross-functional teams to deliver AI-powered products, leveraging technologies like Pytorch and VectorDBs. Responsibilities include building AI foundation models through all development phases (design, training, evaluation, validation, implementation) and conducting applied research to integrate AI advancements into customer experiences. Requires a deep understanding of AI methodologies, experience building large deep learning models (language, images, events, graphs), and expertise in areas like training optimization, self-supervised learning, robustness, explainability, or RLHF. A track record of delivering models at scale and contributing to research through publications or projects is essential.

Applied Researcher I role focused on building AI foundation models through all phases of development, from design through training, evaluation, validation, and implementation. The role involves high-impact applied research to push state-of-the-art AI into customer experiences, with a strong emphasis on delivering models at scale and potentially contributing to publications.

Applied Researcher II at Capital One focused on building AI foundation models and delivering them at scale for customer-facing products. The role involves partnering with cross-functional teams, leveraging technologies like Pytorch and VectorDBs, and engaging in applied research to push AI capabilities.

Applied Researcher I role focused on building AI foundation models through all phases of development, from design through training, evaluation, validation, and implementation. The role involves high-impact applied research to push the latest AI developments into customer experiences, leveraging technologies like Pytorch, AWS, Huggingface, and VectorDBs. Requires a PhD or MS with experience in AI/ML, with expertise in areas like training optimization, self-supervised learning, robustness, explainability, or RLHF, and a track record of delivering models at scale.

Applied Researcher focused on building AI foundation models from design through training, evaluation, validation, and implementation. The role involves applied research to push AI developments into customer experiences, leveraging technologies like Pytorch, AWS, Huggingface, and VectorDBs. Requires experience building large deep learning models and delivering models at scale.

Applied Researcher II at Capital One focused on partnering with cross-functional teams to deliver AI-powered products. The role involves leveraging technologies like Pytorch and VectorDBs, building AI foundation models through all development phases, and engaging in applied research to advance customer experiences. Requires a deep understanding of AI methodologies, experience building large deep learning models, and a track record of delivering models at scale.

The role is for a Distinguished AI Engineer focused on building an enterprise Generative AI Platform. The engineer will design the agentic workflow framework, shared services (memory, guardrails, vector search, SDKs), and blueprints to enable product teams to compose AI capabilities. Key responsibilities include evaluating agentic frameworks, developing an end-to-end GenAI SDK/CLI, implementing central guardrail services, optimizing orchestration for performance, and mentoring other engineers. The role emphasizes creating scalable, safe, and explainable AI solutions for millions of users.

Senior Distinguished AI Engineer role focused on designing, developing, testing, deploying, and supporting AI software components including foundation model training, LLM inference, similarity search, guardrails, model evaluation, experimentation, governance, and observability. The role involves inventing and introducing state-of-the-art LLM optimization techniques to improve performance (scalability, cost, latency, throughput) of large-scale production AI systems, and contributing to the technical vision and roadmap of foundational AI systems. Requires strong engineering and mathematics foundation, expertise in hardware, software, and AI, and experience with cloud platforms and programming languages like Python, Go, Scala, or Java.

Lead AI Engineer role focused on building and deploying AI-powered products and foundational AI systems. Responsibilities include designing, developing, testing, deploying, and supporting AI software components such as foundation model training, LLM inference, similarity search, guardrails, model evaluation, experimentation, governance, and observability. The role involves optimizing LLM performance for scalability, cost, latency, and throughput using various AI technologies and cloud platforms.

Senior Lead AI Engineer focused on AI Foundations, LLM Core, and Agentic AI. The role involves designing, developing, testing, deploying, and supporting AI software components including foundation model training, LLM inference, similarity search, guardrails, model evaluation, experimentation, governance, and observability. It also focuses on optimizing LLM performance (scalability, cost, latency, throughput) for production AI systems and contributing to the technical vision and roadmap of foundational AI systems.

This role focuses on engineering and optimizing AI software components, particularly large language model inference and related platform services, to improve performance, scalability, cost, and latency in a production environment. It involves designing, developing, testing, deploying, and supporting these components, leveraging various AI technologies and cloud platforms.

Senior Manager AI Engineer role focused on building and deploying GenAI Platform Services. Responsibilities include overseeing AI software components like foundation model training, LLM inference, similarity search, guardrails, and model evaluation. The role involves making build-vs-buy decisions, optimizing LLM performance, and contributing to the technical vision of foundational AI systems. Requires people leadership and experience in deploying scalable AI solutions on cloud platforms.

Senior Lead AI Engineer responsible for designing, developing, testing, deploying, and supporting AI software components including foundation model training, large language model inference, similarity search, guardrails, model evaluation, experimentation, governance, and observability. The role involves optimizing LLM performance for scalability, cost, and latency, and contributing to the technical vision and roadmap of foundational AI systems.

Applied Researcher I role focused on building AI foundation models, engaging in applied research to push AI developments into customer experiences, and delivering models at scale. Requires experience in training optimization, self-supervised learning, robustness, explainability, or RLHF, with a track record of delivering libraries or platform code.

Capital One is seeking a Sr. Distinguished Engineer to lead the development and scaling of agentic AI systems for business card marketing, underwriting, and sales. The role involves defining technical strategy, hands-on prototyping, and influencing enterprise architecture to create hyper-personalized marketing systems, assistive technologies, and autonomous sales agents.

Distinguished Engineer role focused on building and scaling agentic AI systems for marketing and sales within an enterprise context. Responsibilities include prototyping, defining technical strategy, influencing architecture, and mentoring teams, with a focus on real-time, hyper-personalized customer engagement and assistive technologies for sales teams.

Lead AI Engineer focused on LLM inference and optimization for AI-powered products within a large enterprise. The role involves designing, developing, and deploying AI software components, with a strong emphasis on improving the performance, scalability, cost, and latency of production AI systems.

Senior Lead AI Engineer role focused on building and deploying Gen AI platform services, including agentic AI systems. Responsibilities span foundation model training, LLM inference, similarity search, guardrails, evaluation, experimentation, governance, and observability, leveraging technologies like AWS, Huggingface, VectorDBs, and Nemo Guardrails. The role emphasizes optimizing large-scale production AI systems for performance, cost, and latency, and contributing to the technical vision and roadmap for foundational AI systems.

Senior Lead AI Engineer focused on AI Foundations, LLM Core, and Agentic AI. The role involves designing, developing, testing, deploying, and supporting AI software components including foundation model training, LLM inference, similarity search, guardrails, model evaluation, governance, and observability. It also requires inventing and introducing LLM optimization techniques to improve performance (scalability, cost, latency, throughput) of large-scale production AI systems. The role leverages AI technologies like AWS Ultraclusters, Huggingface, VectorDBs, Nemo Guardrails, and PyTorch.

This role focuses on designing, developing, testing, deploying, and supporting AI software components, including foundation model training, LLM inference, similarity search, guardrails, model evaluation, experimentation, governance, and observability. The engineer will also invent and introduce LLM optimization techniques to improve the performance (scalability, cost, latency, throughput) of large-scale production AI systems, leveraging technologies like AWS Ultraclusters, Huggingface, VectorDBs, and Nemo Guardrails. The role is within the Intelligent Foundations and Experiences (IFX) team, aiming to advance AI science and engineering and deploy proprietary solutions.

Lead AI Engineer role focused on building and deploying AI-powered products, including foundation model training, LLM inference, similarity search, guardrails, and model evaluation. The role involves leveraging AI technologies like AWS Ultraclusters, Huggingface, VectorDBs, and Nemo Guardrails, and optimizing LLM performance for scalability, cost, and latency. The position requires a strong engineering foundation and experience in AI/ML algorithm development and deployment on cloud platforms.

Senior Lead AI Engineer role focused on AI Foundations, LLM Core, and Agentic AI. Responsibilities include designing, developing, testing, deploying, and supporting AI software components like foundation model training, LLM inference, similarity search, guardrails, model evaluation, and governance. The role involves optimizing LLM performance for scalability, cost, and latency, and contributing to the technical vision for foundational AI systems. It requires experience with cloud platforms and AI/ML algorithms, particularly LLM inference, similarity search, vector databases, and guardrails.

Lead AI Engineer focused on AI Foundations, LLM Core, and Agentic AI. The role involves designing, developing, testing, deploying, and supporting AI software components including foundation model training, LLM inference, similarity search, guardrails, model evaluation, experimentation, governance, and observability. Key responsibilities include optimizing LLM performance for scalability, cost, latency, and throughput using various AI technologies and techniques.

Senior Lead AI Engineer focused on LLM customization and finetuning within Capital One's Intelligent Foundations and Experiences (IFX) team. The role involves designing, developing, testing, deploying, and supporting AI software components including foundation model training, LLM inference, similarity search, guardrails, model evaluation, experimentation, governance, and observability. It requires leveraging AI technologies like Huggingface, VectorDBs, and PyTorch, and optimizing LLM performance for scalability, cost, latency, and throughput in production AI systems. The candidate should have a strong engineering and mathematics foundation, experience with cloud platforms, and the ability to lead and mentor teams.

This role focuses on designing, developing, testing, deploying, and supporting AI software components, including foundation model training, LLM inference, similarity search, guardrails, model evaluation, experimentation, governance, and observability. The engineer will invent and introduce state-of-the-art LLM optimization techniques to improve the performance of large-scale production AI systems and contribute to the technical vision and roadmap of foundational AI systems. The role involves leveraging various AI technologies and optimizing for scalability, cost, latency, and throughput.

Lead AI Engineer role focused on designing, developing, testing, deploying, and supporting AI software components including foundation model training, LLM inference, similarity search, guardrails, model evaluation, experimentation, governance, and observability. The role involves leveraging AI technologies and optimizing LLM performance for scalability, cost, latency, and throughput within an enterprise AI context. The position emphasizes building AI-powered products and foundational AI systems for millions of customers.

Senior Manager, Data Scientist for the Generative AI Systems (Genesis) team within Capital One's US Card division. This role focuses on building and delivering state-of-the-art generative AI-based solutions for various applications including dialogue, text summarization, reading comprehension, speech recognition, image/document processing, and time-series modeling. The goal is to enhance both internal business efficiency and customer-facing experiences. The role involves partnering with cross-functional teams, leveraging a broad tech stack, and building ML models through all phases of development.

Senior Lead AI Engineer focused on AI Foundations, LLM Core, and Agentic AI. The role involves designing, developing, testing, deploying, and supporting AI software components including foundation model training, LLM inference, similarity search, guardrails, model evaluation, experimentation, governance, and observability. It also includes optimizing LLM performance for scalability, cost, latency, and throughput using various AI technologies and cloud platforms. The role emphasizes building responsible and reliable AI systems for banking applications.

Applied Researcher focused on building multi-agent AI systems, leveraging knowledge graphs, GraphRAG, Graph-of-Thought, LangGraph, and agent protocols to transform the software development lifecycle. The role involves applied research, model development, and delivering AI-powered products.

Lead AI Engineer focused on AI Foundations, LLM Core, and Agentic AI. The role involves designing, developing, testing, deploying, and supporting AI software components including foundation model training, LLM inference, similarity search, guardrails, model evaluation, experimentation, governance, and observability. It also includes optimizing LLM performance for scalability, cost, latency, and throughput using various AI technologies and techniques.

Senior Lead AI Engineer focused on AI Foundations, LLM Core, and Agentic AI. The role involves designing, developing, testing, deploying, and supporting AI software components including foundation model training, LLM inference, similarity search, guardrails, model evaluation, and observability. It also emphasizes inventing and introducing LLM optimization techniques to improve the performance of large-scale production AI systems.

Lead AI Engineer role focused on building and deploying AI-powered products, including foundation model training, LLM inference, similarity search, guardrails, and evaluation. The role involves optimizing performance, scalability, cost, and latency of large-scale production AI systems using various AI technologies and cloud platforms.

Manager, Data Science - AI Foundations role at Capital One focuses on building and shipping AI/ML solutions for customer-facing applications, including personalization and digital assistants. The role involves leveraging LLMs, fine-tuning them, and building ML/NLP models through all development phases, from design to production operationalization. It emphasizes partnering with cross-functional teams and utilizing technologies like PyTorch, AWS, Hugging Face, LangChain, and VectorDBs.

This role focuses on building and shipping AI/ML solutions for Capital One's mobile app, leveraging LLMs and generative AI. The Principal Data Scientist will partner with cross-functional teams to deliver AI-powered products, adapt and fine-tune LLMs for customer-facing applications, and build ML/NLP models through all phases of development, including training, evaluation, and validation, with a strong emphasis on operationalizing them in production systems serving millions of customers. Experience in training language models, computer vision models, and expertise in areas like training optimization, self-supervised learning, explainability, and RLHF are required, along with a track record of delivering models at scale.

Senior Manager, Data Science - AI Foundations role at Capital One, focusing on building and shipping AI/ML solutions for their mobile app. The role involves partnering with cross-functional teams, leveraging technologies like PyTorch, AWS, Hugging Face, LangChain, and VectorDBs, and specializing in NLP and LLMs for customer-facing applications. Responsibilities include model development from design to production, operationalization, and translating complex work into business goals. The ideal candidate is customer-first, innovative, creative, a leader, technical with hands-on LLM experience, and influential. Experience in training language models, computer vision models, and expertise in areas like training optimization, self-supervised learning, explainability, and RLHF is required, along with a track record of delivering models at scale in both training and inference.

Senior Lead AI Engineer focused on optimizing LLM inference performance, scalability, cost, and latency for production AI systems within Capital One's Intelligent Foundations and Experiences (IFX) team. The role involves designing, developing, and deploying AI software components, including foundation model training, inference, similarity search, guardrails, evaluation, and observability, leveraging cloud platforms and open-source AI technologies.

Lead AI Engineer focused on optimizing LLM inference for scalability, cost, and latency within an enterprise AI setting. The role involves designing, developing, and deploying AI software components, including foundation model training, inference services, similarity search, guardrails, and model evaluation, leveraging cloud platforms and various AI technologies.

Senior Lead AI Engineer role focused on AI Foundations, LLM Core, and Agentic AI. Responsibilities include designing, developing, testing, deploying, and supporting AI software components such as foundation model training, LLM inference, similarity search, guardrails, model evaluation, and agentic systems. The role involves optimizing LLM performance for scalability, cost, and latency, and contributing to the technical vision and roadmap for foundational AI systems. Requires strong engineering and mathematics foundation, expertise in Python/Go/Scala/Java, and experience with cloud platforms and AI technologies like Huggingface, VectorDBs, and PyTorch.

Lead AI Engineer role focused on building and deploying AI-powered products, including foundation model training, LLM inference, similarity search, guardrails, and model evaluation. The role involves leveraging AI technologies like AWS Ultraclusters, Huggingface, VectorDBs, and Nemo Guardrails, and optimizing LLM performance for scalability, cost, and latency. The position requires a strong engineering foundation and experience in AI/ML algorithm development and deployment on cloud platforms.

Lead AI Engineer role focused on building and deploying AI-powered products, including foundation model training, LLM inference, similarity search, guardrails, and model evaluation. The role involves leveraging AI technologies like AWS Ultraclusters, Huggingface, VectorDBs, and Nemo Guardrails, and optimizing LLM performance for scalability, cost, and latency. The position requires a strong engineering foundation and experience in AI/ML algorithm development and deployment on cloud platforms.

Director of AI Engineering responsible for the strategic vision, development, and management of autonomous AI systems and platforms, with a focus on agentic workflows and ensuring compliance with regulations and ethical AI best practices within a fintech domain.

Capital One's LLM Customization team is seeking a Principal Associate Data Scientist to work on GenAI models. The role involves creating high-quality data for training and testing, building capabilities for evaluating and monitoring generative models, and developing horizontal capabilities like search, summarization, RAG, and agentic workflows for production applications. The candidate will partner with cross-functional teams, leverage technologies like Pytorch, AWS, Hugging Face, LangChain, and VectorDBs, and adapt/finetune LLMs for customer-facing applications. Responsibilities include building ML and NLP models through all development phases, from design to evaluation and validation, and operationalizing them in production systems serving over 80 million customers. Experience in training language models, explainability, RLHF, and delivering models at scale is required.

Senior Lead AI Engineer focused on AI Foundations, LLM Core, and Agentic AI. The role involves designing, developing, testing, deploying, and supporting AI software components including foundation model training, LLM inference, similarity search, guardrails, model evaluation, experimentation, governance, and observability. It also focuses on optimizing LLM performance (scalability, cost, latency, throughput) for production AI systems and contributing to the technical vision and roadmap of foundational AI systems.

Senior Lead AI Engineer focused on AI Foundations, LLM Core, and Agentic AI. The role involves designing, developing, testing, deploying, and supporting AI software components including foundation model training, LLM inference, similarity search, guardrails, model evaluation, experimentation, governance, and observability. It also focuses on optimizing LLM performance (scalability, cost, latency, throughput) for production AI systems and contributing to the technical vision and roadmap of foundational AI systems.

Senior Distinguished Engineer focused on architecting and building the AI compute infrastructure for Capital One's enterprise machine learning platform. This role involves developing scalable, high-performance systems for diverse AI workloads including LLM pre-training, fine-tuning, inference, and agentic applications, leveraging distributed compute frameworks like Ray and Spark on cloud substrates.

Senior Lead AI Engineer role focused on building and deploying AI-powered products and foundational AI systems, including LLM inference, agentic AI, similarity search, guardrails, and model evaluation. The role involves optimizing performance, scalability, cost, and latency of large-scale production AI systems.

Lead AI Engineer focused on AI Foundations, LLM Customization and Finetuning within Capital One's Intelligent Foundations and Experiences (IFX) team. The role involves designing, developing, testing, deploying, and supporting AI software components including foundation model training, LLM inference, similarity search, guardrails, model evaluation, governance, and observability. It requires leveraging AI technologies like AWS Ultraclusters, Huggingface, VectorDBs, and Nemo Guardrails, and inventing optimization techniques for performance, scalability, cost, latency, and throughput of large-scale production AI systems. The role also contributes to the technical vision and roadmap of foundational AI systems.

Machine Learning Engineer focused on productionizing ML models and systems at scale within a fintech company. Responsibilities include designing, building, and delivering ML models, informing ML infrastructure decisions, writing and testing code, automating tests and deployment, retraining/maintaining/monitoring models in production, leveraging cloud architectures, constructing data pipelines, and ensuring code quality and model governance. The role emphasizes experience with ML frameworks, productionizing models, and cloud-based ML systems.

Lead Data Scientist role focused on developing and deploying deep learning models for underwriting capabilities in a fintech company. The role involves advancing existing models, building neural networks, transforming multi-modal inputs, and driving projects from prototype to production. Requires experience in sequential data, model development leadership, and modern ML frameworks.

Manager, Data Scientist role focused on building and deploying machine learning models for credit card customer acquisitions in the fintech domain. The role involves the full model lifecycle, from design and training to evaluation, validation, and implementation, with a focus on delivering customer-facing products.

Develop and maintain machine learning models for underwriting in the financial services market, focusing on feature engineering, insight generation, and handling various data types including sequential and multi-modal data. Requires strong statistics, ML, Python, and Model Risk Management experience.

This role focuses on building and challenging existing statistical and machine learning models within the credit review domain at Capital One. The Senior Manager will lead a team, leverage technologies like Python, AWS, and Spark, and partner with cross-functional teams to deliver data-driven solutions that impact risk management and enterprise outcomes. The role requires strong technical and statistical skills, with experience in model building, validation, and various ML techniques.

Lead Software Engineer for the Machine Learning eXperience (MLX) team at Capital One India. This role focuses on building and deploying responsible GenAI and ML models, educating associates on AI platforms, driving innovation, and integrating AI into company products. The role involves leading technology projects, partnering with product/design, collaborating across Agile teams, developing features, sharing technical knowledge, and debugging distributed systems. Requires extensive experience in software engineering, backend services, databases, technical leadership, data-intensive solutions, SDKs, and deploying ML platform solutions in the cloud. Preferred qualifications include MLOps, production-ready capabilities, responsible AI implementation, and exposure to Generative AI, LLMs, LangChain, and vector databases.

Capital One is seeking a Principal Data Scientist to build machine learning models for bank operations, focusing on payment channels, anomaly detection, and operational streamlining with agentic processes. The role involves leveraging Python, Snowflake, and various ML technologies including LLMs and transformer architectures.

Senior Manager for Model Risk Office at Capital One, focusing on identifying and quantifying risks associated with models, including Generative AI. The role involves building ML models to challenge existing production models and contributing to the governance framework for future models. It requires validating models across various business domains and communicating risks to executives. The ideal candidate is innovative, creative, a leader, technically proficient, statistically minded, and skilled in handling large datasets.

Senior Lead Machine Learning Engineer at Capital One, focused on productionizing ML applications and systems at scale within a fintech domain. Responsibilities include designing, building, and delivering ML models, optimizing ML infrastructure, writing and testing code, automating deployment, and maintaining models in production. The role involves leveraging cloud platforms, constructing data pipelines, and ensuring responsible AI practices.

Lead Machine Learning Engineer at Capital One, focused on architecting and productionizing intelligent systems for Capital One Travel's luxury market. The role involves designing, building, and delivering ML models and components, informing ML infrastructure decisions, writing and testing application code, automating tests and deployment, and leveraging cloud-based architectures to deliver optimized ML models at scale. Responsibilities include retraining, maintaining, and monitoring models in production, constructing data pipelines, and ensuring adherence to CI/CD, Responsible AI, and Explainable AI best practices.

Lead Machine Learning Engineer at Capital One, focused on productionizing ML applications and systems at scale. Responsibilities include designing, building, and delivering ML models, developing ML infrastructure, writing and testing code, automating tests and deployment, and leveraging cloud-based architectures. The role emphasizes CI/CD, responsible AI, and optimized data pipelines for ML models.

Data Scientist role focused on building and deploying machine learning models for fraud detection in the Small Business Bank (SBB) at Capital One. The role involves working with large datasets, applying various ML techniques, and collaborating with cross-functional teams to protect customers and the company from financial fraud.

Lead Machine Learning Engineer at Capital One, focused on productionizing ML applications and systems at scale within an Agile team. Responsibilities include designing, building, and delivering ML models, informing infrastructure decisions, writing and testing code, automating tests and deployment, retraining/maintaining/monitoring production models, leveraging cloud architectures, constructing data pipelines, and ensuring code quality, model governance, and adherence to Responsible and Explainable AI best practices.

Capital One is seeking a Manager, Data Scientist for their Credit Review Models, Data and Innovative solutions team. The role involves building statistical and machine learning models to challenge existing production models, leveraging technologies like Python, AWS, and Spark. The candidate will partner with cross-functional teams to deliver innovative solutions in risk management and enterprise decision-making. The role requires a strong statistical background, experience with machine learning, and proficiency in open-source tools and cloud platforms.

Capital One is seeking a Manager, Data Scientist for their Bureau Data Strategy team. This role involves partnering with cross-functional teams to deliver products, leveraging technologies like Python, AWS, and Spark to analyze large datasets, and building machine learning models through all phases of development. The ideal candidate is customer-focused, a leader, technically proficient with open-source tools and cloud platforms, and skilled in data analysis.

Lead Software Engineer to build an AI-powered marketing content layer, integrating LLMs into content generation, channel-specific builds, and AI-assisted compliance workflows. The role involves developing multi-agent orchestration systems, evaluation/observability tooling, and guardrail frameworks for LLM outputs, with a focus on enterprise AI applications.

Lead AI Engineer focused on AI Foundations, LLM Customization and Finetuning within Capital One's Intelligent Foundations and Experiences (IFX) team. The role involves designing, developing, testing, deploying, and supporting AI software components including foundation model training, LLM inference, similarity search, guardrails, model evaluation, governance, and observability. It requires leveraging AI technologies like AWS Ultraclusters, Huggingface, VectorDBs, and Nemo Guardrails, and inventing optimization techniques for performance, scalability, cost, latency, and throughput of large-scale production AI systems. The role also contributes to the technical vision and roadmap of foundational AI systems.

Senior Machine Learning Engineer at Capital One focused on productionizing ML applications and systems at scale. Responsibilities include designing, building, and delivering ML models, informing ML infrastructure decisions, writing and testing code, automating tests and deployment, retraining/maintaining/monitoring models in production, leveraging cloud architectures, constructing data pipelines, and ensuring code quality and model governance. Requires experience with ML frameworks, productionizing models, and cloud-based ML systems.

This role focuses on building machine learning models for corporate strategy within a financial services company. It involves leveraging data science skills to analyze consumer behavior, market conditions, and peer performance, and translating complex work into tangible business goals. The role requires experience across the full ML development lifecycle, from design through implementation, using technologies like Python, AWS, and Spark.

This role focuses on applying generative AI and LLMs to unstructured data (text, image) for enterprise applications in areas like customer servicing and document processing. It involves building and operationalizing ML/NLP models, assessing production architectures, defining AI observability, and evaluating AI system behavior. The role emphasizes practical application and scaling AI adoption within a regulated financial environment.

Senior Manager, Machine Learning Engineering at Capital One, focused on productionizing ML applications and systems at scale within a fintech domain. The role involves designing, building, and delivering ML models, managing ML infrastructure, optimizing data pipelines, and ensuring the performance and availability of ML applications in production. It requires people management experience and collaboration with cross-functional Agile teams.

Senior Machine Learning Engineer focused on building, scaling, and optimizing ML systems and applications within enterprise platforms. Responsibilities include designing, developing, and deploying ML models, constructing data pipelines, and ensuring high availability and performance of ML applications using cloud-based architectures and CI/CD best practices.

Seeking a Senior Director of Software Engineering to lead a team in redefining software development speed and quality using AI-native workflows and agentic development tools. The role involves a 'Player-Coach' approach, shipping production code, mentoring engineers, and ensuring AI-generated output is flawless, secure, and scalable. The focus is on bridging the gap between Intent and Execution (I=E) through rigorous, spec-driven design.

Seeking a Director of Software Engineering to lead a team in redefining software development speed and quality using AI-native workflows and agentic development tools. The role involves a 'Player-Coach' approach, shipping production-ready code, mentoring engineers, and ensuring AI-generated output is flawless, secure, and scalable.

Seeking a Director of Software Engineering to lead a team in redefining software development speed and quality using AI-native workflows and agentic development tools. The role involves a 'Player-Coach' approach, shipping production-ready code, mentoring engineers, and ensuring AI-generated output is flawless, secure, and scalable.

Senior Lead Machine Learning Engineer role focused on productionizing ML applications and systems at scale within a fintech domain. Responsibilities include designing, building, and delivering ML models, optimizing ML infrastructure, writing and testing code, automating tests and deployment, and maintaining models in production using cloud-based architectures and CI/CD best practices. The role also involves constructing data pipelines and ensuring responsible AI practices.

This role is for a Distinguished Software Engineer focused on building and scaling the foundational compute infrastructure for an enterprise AI+ML platform. The engineer will work on distributed systems, cloud technologies, and support various AI/ML workloads including LLM pre-training, fine-tuning, inference, and agentic applications.

Distinguished Engineer role focused on building an AI-powered platform for business process automation and intelligent finance, with a strong emphasis on agentic patterns and real-time observability. The role involves technical leadership, strategy, and hands-on contribution to complex problems in a regulated fintech environment.

Capital One is seeking a Principal Associate, Data Scientist for their US Card Marketing Intelligence team. This role involves building machine learning models for marketing optimization, leveraging a broad technology stack including Python, AWS, H2O, and Spark. The ideal candidate will have a strong statistical background, experience with various ML techniques, and the ability to translate complex work into business goals.

This role is for a Principal Associate Data Scientist in Capital One's Innovation Hub, focusing on designing and deploying generative AI applications and AI-powered capabilities to solve business challenges. The role involves building machine learning models through all development phases and leveraging technologies like Python, AWS, and Spark. Experience with generative AI, LLMs, and AWS (including Bedrock) is preferred.

This role is for a Principal Associate Data Scientist on the Generative AI Systems (Genesis) team within Capital One's Card Data Science division. The team builds state-of-the-art generative AI solutions for various applications including dialogue, text summarization, reading comprehension, speech recognition, image/document processing, and time-series sequencing. The role involves partnering with cross-functional teams to deliver customer-facing and internal applications, leveraging technologies like Python, AWS, and Spark, and building machine learning models through all phases of development. The ideal candidate is customer-focused, innovative, creative, technically proficient, statistically-minded, and adept at handling large datasets.

Manager of Data Science for Consumer Identity Machine Learning team within Capital One's AI foundation organization. The role focuses on delivering real-time, personalized customer experiences by building and operationalizing machine learning models that use vast amounts of customer data to anticipate needs, fight fraud, and improve digital experiences. The role involves working across the data science lifecycle, from design and training to evaluation and production deployment, partnering with product and engineering teams to serve over 50 million customers.

This role focuses on developing and supporting econometric time-series models for balance sheet portfolios within Capital One's Retail and Direct Bank. The Data Scientist will apply quantitative methods to improve business performance, demonstrate a track record in behavior model development, and communicate complex models to various stakeholders including management, model risk office, and regulators. The ideal candidate has hands-on experience with data science solutions using open-source tools and cloud platforms, with specific experience in time series, clustering, classification, sentiment analysis, and deep learning.

This role is for a Senior Manager of Data Science focused on Quantum Computing Research within financial services. The candidate will define and execute a research roadmap for quantum algorithms and applications, collaborate with hardware vendors, and publish findings. The role emphasizes exploring the intersection of quantum computing and AI for financial challenges.

This role focuses on building and implementing ML and NLP models, including LLM-based chatbots and GenAI applications, within the fintech domain for audit and risk management. The position involves the full ML lifecycle from design to productionization and monitoring, leveraging various technologies like Python, Hugging Face, LangChain, and AWS.

This role focuses on building and deploying AI/ML models for Anti-Money Laundering (AML) within a financial services context. The responsibilities include developing production-ready pipelines, building ML models and AI tools, and specifically fine-tuning, evaluating, and productionizing LLMs. The role involves working with technologies like Python, AWS, Spark, and LLM-specific tools such as LangGraph and LlamaIndex, with a strong emphasis on delivering industry-leading risk management products.

Senior Associate Data Scientist role focused on developing and deploying machine learning models for Anti-Money Laundering (AML) detection within a financial services company. The role involves end-to-end model development, including data sourcing, training, evaluation, validation, and implementation, utilizing tools like Python, AWS, and Spark. The primary output is a productionized AI/ML system for risk management.

This role focuses on building and deploying machine learning models for credit card customer acquisitions within the fintech domain. The data scientist will own the full model lifecycle, from design and training to evaluation, validation, implementation, monitoring, and governance. The role involves leveraging Python, AWS, Spark, and H2O to analyze large datasets and develop models for underwriting decisions.

Manager role focused on risk assessment, design reviews, and oversight of AI/ML platforms, specifically Generative AI and Agentic AI systems, within a regulated financial services environment. The role involves collaborating with technical teams to ensure security, reliability, and adherence to risk appetite throughout the AI/ML lifecycle, including defining observability and monitoring requirements for autonomous systems.

Manager, Data Scientist role focused on model risk management within a fintech company. The role involves partnering with cross-functional teams to identify and quantify model risks, building ML models to challenge existing production models, contributing to model governance, and validating various models. Requires strong statistical and data science skills, experience with ML, and open-source tools.

This role is within Capital One's Model Risk Office, specifically supporting the Card Fraud Model Risk team. The primary responsibility is to evaluate model risk associated with fraud models across the customer lifecycle by performing rigorous assessments and building independent challenger models. The role involves building machine learning models through all phases of development, from design through training, evaluation, validation, and implementation, and leveraging technologies like Python, AWS, and Spark.

Director of Product Management for Enterprise AI, focusing on establishing a unified approach to AI within the Associate Experience (AX) tooling. The role involves building trust, maximizing ROI, preventing silos, and empowering associates. Key responsibilities include defining the AI roadmap, leading product execution for AI agents, driving user enablement, and ensuring cross-functional alignment. The role requires blending product execution with strategic vision for seamless, agentic experiences.

Senior Director role responsible for threat detection, cyber logging, privacy breach reporting, and threat hunting, with a focus on driving AI strategy for the cyber detection lifecycle and integrating AI/ML models for advanced threat detection and log management.

Capital One is seeking a Manager, Data Science to lead the LLM Customization team, focusing on bringing LLMs and GenAI to life within the company. The role involves partnering with cross-functional teams to deliver AI-powered products, leveraging technologies like Pytorch, Hugging Face, and LangChain, and specializing in NLP for LLM adaptation and fine-tuning. Responsibilities include building NLP models through development, training, evaluation, and validation, and operationalizing them in production systems. The ideal candidate is innovative, creative, technical, and influential, with experience in training language models, large computer vision models, and delivering models at scale.

Distinguished Engineer role focused on architecting and building AI-driven risk management products within the financial sector. This is a hands-on technical leadership position requiring deep expertise in software engineering, solution architecture, cloud computing, and data architecture, with a strong emphasis on applying AI/ML to solve complex problems and drive innovation in the developer lifecycle and risk management.

This role focuses on developing and implementing machine learning models for credit outcomes forecasting within the US Card Intelligence Segments organization. It involves applying explainability techniques, creating AI-model-based decisioning frameworks in a regulated industry, and collaborating with cross-functional teams. The ideal candidate has strong data analysis, statistical modeling, and machine learning experience, with a preference for applied research and explainability.

Lead Machine Learning Engineer at Capital One focused on productionizing ML applications and systems at scale. Responsibilities include designing, building, and delivering ML models, informing ML infrastructure decisions, writing and testing application code, collaborating with Agile teams, retraining/maintaining/monitoring models in production, leveraging cloud architectures, constructing data pipelines, and ensuring CI/CD best practices. The role emphasizes building, scaling, and optimizing ML systems, with experience in Python/Scala/Java and distributed computing.

Capital One's Emerging ML team is seeking a Manager, Data Science to conduct research and development in AI, focusing on embeddings and foundation models. The role involves building machine learning models from design through production, partnering with product and engineering teams, and analyzing large-scale customer data using tools like Spark and AWS. The ideal candidate is curious, technical, statistically-minded, and customer-oriented, with hands-on experience in data science lifecycle and open-source tools.

Data Scientist role focused on building and implementing machine learning models for fraud detection and authentication within the US Card Fraud Authentication team. The role involves analyzing complex datasets, optimizing authentication decisioning, and staying ahead of evolving fraud patterns using a modern tech stack including Python, AWS, Spark, H2O, and SQL.

Lead Machine Learning Engineer at Capital One focused on productionizing ML applications and systems at scale. Responsibilities include designing, building, and delivering ML models, optimizing ML infrastructure, writing and testing code, automating tests and deployment, and maintaining models in production. The role emphasizes cloud-based architectures, data pipelines, CI/CD, and responsible AI practices.

Lead Machine Learning Engineer at Capital One focused on productionizing ML applications and systems at scale within a fintech domain. Responsibilities include designing, building, and delivering ML models, optimizing ML infrastructure, writing and testing code, automating tests and deployment, retraining and monitoring models in production, leveraging cloud architectures, constructing data pipelines, and ensuring responsible AI practices. Requires experience in data-intensive solutions, programming, and building/scaling ML systems.

Capital One is seeking a Manager, Data Scientist to lead the development of industry-leading machine learning models for credit underwriting decisions within the Business Cards & Payments team. This role involves full-spectrum modeling solutions across customer lifecycles, collaborating with cross-functional teams, and leveraging technologies like Python, AWS, H2O, and Spark to analyze large datasets and implement models. The ideal candidate has a strong statistical background, hands-on experience with ML model development, and a customer-first approach.

Lead Machine Learning Engineer at Capital One focused on productionizing ML applications and systems at scale. Responsibilities include designing, building, and delivering ML models, informing ML infrastructure decisions, writing and testing code, automating tests and deployment, collaborating with cross-functional teams, retraining/maintaining/monitoring production models, leveraging cloud architectures, constructing data pipelines, and ensuring CI/CD best practices, code security, risk governance, and Responsible/Explainable AI. Requires experience in building, scaling, and optimizing ML systems and data-intensive solutions.

This role focuses on building knowledge graphs and graph algorithms for fraud prevention within the financial sector. The Data Scientist will leverage technologies like Python, AWS, Spark, Gremlin, and NeptuneDB to uncover hidden connections in data, pilot graph modeling algorithms through development phases, and partner with cross-functional teams to deliver fraud defenses. The ideal candidate is customer-focused, innovative, technically proficient, and skilled in handling large datasets.

Senior Manager Data Scientist role focused on building and leading a team to develop next-generation machine learning models for credit decisioning, customer valuation, and underwriting within Capital One's US Card Intelligence Segments organization. The role involves leveraging Python, AWS, Spark, and other technologies to build models through all phases of development, from design to implementation, and translating complex work into business goals.

Manager of Data Science focused on AI for Data within a financial services company. The role involves partnering with cross-functional teams to deliver AI-enabled features across the data lifecycle, building machine learning models from design through implementation, and leveraging technologies like Python, Spark, and AWS. Experience with NLP, Information Retrieval, Search, Recommendations, and LLM fine-tuning is preferred.

Data Scientist role focused on applying AI/ML to talent strategy and HR analytics. Responsibilities include building NLP and ML models, using LLMs via prompt engineering and RAG, and partnering with cross-functional teams to deliver HR tools and AI-powered products. Requires experience with Python, SQL, AWS, and ML/AI tools like Hugging Face, VectorDBs, and PyTorch/TensorFlow.

Distinguished Engineer role focused on architecting and building an Agentic AI framework for a Travel Intelligence Platform, integrating ML model development with agentic systems for proactive journey management and growth marketing. Requires expertise in data pipelines, cloud architecture, and leading cross-functional initiatives.

Capital One is seeking a Manager, Data Scientist for their Auto Finance business. This role involves building machine learning models for applications like customer lifetime valuation, product recommendation, fraud detection, and productivity improvement via Generative AI. The candidate will work with a cross-functional team, leverage technologies like Python, AWS, and Spark, and translate complex work into business goals. Requires a strong quantitative background, experience with data analysis, machine learning, and relational databases, with a preference for a PhD and AWS experience.

Data Scientist role at Capital One's Auto Finance business, focusing on building machine learning models for applications like customer lifetime valuation, product recommendation, fraud detection, and marketing optimization. The role involves leveraging technologies like Python, AWS, and Spark, and working through all phases of model development from design to implementation.

The role focuses on building and implementing machine learning models for credit decisioning within the Mainstreet Acquisitions team at Capital One. It involves working with large datasets, leveraging various technologies, and collaborating with cross-functional teams to deliver solutions for critical business decisions like application approval and customer valuation.

Manager, Data Science role at Capital One in Plano, TX. This position involves partnering with cross-functional teams to deliver products, leveraging technologies like Python, AWS, and Spark. The core responsibilities include building machine learning models through all development phases (design, training, evaluation, validation, implementation) and translating complex work into business goals. Requires a quantitative background with experience in data analytics, machine learning, and relational databases.

Lead Machine Learning Engineer responsible for productionizing ML applications and systems at scale, including designing, building, and delivering ML models, optimizing ML infrastructure, developing data pipelines, and maintaining models in production within a cloud-based environment. The role emphasizes engineering best practices for ML systems.

Lead Machine Learning Engineer focused on productionizing ML applications and systems at scale within an enterprise environment. Responsibilities include designing, building, and delivering ML models, optimizing ML infrastructure, writing and testing application code, automating tests and deployment, and maintaining models in production using cloud-based architectures and CI/CD best practices.

Distinguished Engineer role focused on architecting and leading the evolution of content generation, storage, and retrieval platforms at scale, integrating AI to empower marketers within a regulated fintech environment. The role involves defining technical direction, prototyping, and collaborating with product and AI teams, with a strong emphasis on LLM systems, RAG, and prompt tooling.

This role focuses on ensuring the security of AI/ML and agentic AI solutions within Capital One's AIML Division. The Senior Manager will lead the development of secure AI/ML and agentic AI solutions, establish AI-First SDLC practices, design security controls, conduct threat modeling, define guardrails, and advise leadership on AI cybersecurity risks and strategy.

This Business Manager role at Capital One India focuses on modernizing Anti-Money Laundering (AML) processes using advanced analytics, data science, and machine learning models. The team develops data sourcing, predictive models, monitoring, and reporting solutions, with responsibilities including strategic leadership, execution of business requirements, partnership with various departments, and a strong analytical orientation. The role requires experience in quantitative fields, analytics, and ideally econometric/statistical techniques and model development, with a focus on risk management and financial services.

Capital One is seeking a Principal Data Scientist to build and implement machine learning models for real-time credit underwriting decisions within their Business Card & Payments team. The role involves leveraging Python, AWS, and Spark to develop models from design through implementation, working with large datasets, and translating complex work into business goals. Experience with classification, sentiment analysis, time series, and deep learning is expected.

Distinguished Data Engineer role focused on designing and implementing scalable data architectures, optimizing data pipelines, and leading the development of agentic workflows within an enterprise data ecosystem. The role involves integrating AI/ML into operations for predictive and automated platform capabilities, with a strong emphasis on Databricks, Snowflake, and AWS.

Lead Software Engineer to build an AI-powered marketing content layer, integrating LLMs into content generation, channel-specific builds, and AI-assisted compliance workflows. The role involves developing multi-agent orchestration systems for content review and dispatch, building evaluation and observability tooling for LLM outputs, and defining guardrail frameworks.

Data Scientist role focused on modernizing loss forecasting and data transformation within Capital One's credit risk management team. The role involves building statistical/machine learning models to challenge existing production models, contributing to model governance, and presenting model risks to executives. Requires experience with Python, AWS, Spark, and machine learning, with a strong statistical background and ability to handle large datasets.

Lead Software Engineer to build an AI-powered marketing content layer, integrating LLMs into content generation, channel-specific builds, and AI-assisted compliance workflows. The role involves developing multi-agent orchestration systems for content review and dispatch, building evaluation and observability tooling for LLM outputs, and defining guardrail frameworks.

Capital One is seeking a Manager, Data Scientist to lead the development and deployment of machine learning models for their Credit Line Increase Program. This role involves partnering with cross-functional teams, leveraging technologies like Python and AWS, and managing the full model lifecycle from design to implementation and monitoring. The ideal candidate has a strong statistical background, experience with various ML techniques, and a customer-centric approach.

Lead Software Engineer role focused on architecting and launching conversational AI experiences powered by Generative AI for Capital One customers. The role involves leading a team, collaborating with product managers, and delivering cloud-based solutions using various programming languages and AWS services.

Distinguished Engineer role focused on architecting and leading the end-to-end execution of AI applications, specifically an agentic orchestration system for marketing technology. The role involves scaling from MVP to a sophisticated system, leveraging a diverse data ecosystem including vector stores, and driving engineering excellence with Gen AI coding tools.

Sr. Director, Machine Learning Engineering to lead and scale a high-performing engineering organization responsible for the Personalization Platform. This role defines technical strategy, delivery roadmap, and operating model for recommendation systems, ranking, decisioning, GenAI infrastructure, MLOps, and low-latency serving systems. Responsibilities include building and developing engineers, partnering cross-functionally, driving ML infrastructure and pipelines, architecting low-latency systems, evolving MLOps, guiding AI/LLM optimization, and providing technical and people leadership.

Lead Software Engineer to build an AI-powered marketing content layer, integrating LLMs into content generation, channel-specific builds, and AI-assisted compliance workflows. The role involves developing multi-agent orchestration systems for content review and dispatch, and building evaluation/observability tooling for LLM outputs.

Lead Software Engineer to build an AI-powered marketing content layer, focusing on LLM-integrated content generation, channel-specific content builds, AI-assisted compliance, and multi-agent orchestration for marketing content across various channels.

This role involves building and challenging statistical and machine learning models in a fintech environment, focusing on credit review and risk management. The candidate will leverage technologies like Python, AWS, and Spark, and collaborate with cross-functional teams to deliver data-driven solutions. The role requires a strong statistical background, experience with machine learning, and a proactive approach to evaluating and improving existing models.

Lead Machine Learning Engineer focused on MLOps, building Kubernetes clusters, and deploying ML models at scale on AWS for a fintech company. The role involves designing, building, and maintaining ML infrastructure and pipelines, collaborating with data science and product teams, and ensuring the performance, reliability, and responsible deployment of ML systems.

Principal Data Scientist role focused on building and managing machine learning models for customer management within a fintech company. The role involves the full lifecycle of model development, from design and training to evaluation, validation, and implementation, leveraging technologies like Python, AWS, and Spark.

Data Scientist role focused on developing AI-enabled features across the data lifecycle within a fintech company. Responsibilities include building ML models through all phases, leveraging technologies like Python, AWS, and Spark, and collaborating with cross-functional teams. Requires experience with various ML techniques, deep learning frameworks, and NLP/IR/Search/Recommendations/Fine-tuning on LLMs.

Sr. Director of Product Management to lead a team responsible for Capital One's Machine Learning and Generative AI platforms, focusing on core platform services for AI/ML that power business applications. Requires technical leadership, experience building products for data scientists and software developers, and familiarity with AI/ML infrastructure and tooling.

Distinguished Engineer role focused on architecting and leading the end-to-end execution of AI applications, specifically an agentic orchestration system for marketing technology. The role involves scaling from MVP to a sophisticated system, leveraging a diverse data ecosystem including vector stores, and driving engineering excellence with Gen AI coding tools.

Senior Manager, Data Science role at Capital One focused on building Generative AI models and products for financial services. The role involves partnering with cross-functional teams, leveraging technologies like Python and AWS, and working across the full development lifecycle from design to monitoring. Emphasis on LLM prompting/fine-tuning and GenAI application development.

This role focuses on the engineering aspects of machine learning, specifically in productionizing ML applications and systems at scale within a financial services context. The engineer will be involved in the design, development, implementation, and maintenance of ML models and infrastructure, ensuring high availability and performance. The role emphasizes collaboration, code quality, and leveraging cloud platforms for ML deployment.

Capital One is seeking a Director, Data Scientist to lead efforts in transforming how next-generation models are built and trained for the US Card business. This role involves leveraging machine learning and AI techniques to innovate credit forecasting, working with a cross-functional team, and managing the full lifecycle of model development from design through implementation. The position requires a strong quantitative background, experience in data analytics, machine learning, and relational databases, with a focus on innovation and leadership.

Capital One's DataLabs AML team is modernizing money laundering detection using advanced analytics, statistics, and machine learning models. This Principal Data Scientist role involves end-to-end development, deployment, and monitoring of risk management models, partnering cross-functionally, and defending these systems to regulators. The role requires strong ML/statistical skills, experience with Python/R, and SQL, with a focus on building and validating predictive models in the financial services domain.

Senior Manager, Data Science for Cash Flow Underwriting at Capital One. This role focuses on leveraging advanced machine learning techniques to build and implement predictive models for risk and usage, transforming raw banking data into valuable features for forecasting creditworthiness and customer behavior. The role involves leading a team, strategic planning, and end-to-end model development.

This role focuses on deploying, optimizing, and modernizing machine learning model pipelines and execution platforms for consumer credit risk management within a fintech company. The primary responsibility is to ensure these models are effectively implemented and provide insights for strategic decision-making, including loss allowances, stress testing, and capital allocation.

Data Scientist role focused on building machine learning models for cash flow underwriting in the fintech domain. The role involves transforming raw banking data into predictive features to forecast creditworthiness and customer behavior, covering all phases of model development from design to implementation.

This role focuses on leveraging advanced machine learning techniques to identify and engineer predictive signals from cash flow and transaction data for risk and usage models in the fintech domain. The data scientist will transform raw banking data into high-value features to forecast creditworthiness and customer behavior, building ML models through all phases of development.

Data Scientist role focused on building machine learning models for financial services applications like customer lifetime valuation, product recommendation, and fraud detection, with a specific mention of Generative AI. The role involves the full ML lifecycle from design to implementation and requires experience with Python, SQL, AWS, and various ML techniques.

This Business Manager role focuses on strategic leadership and execution within Capital One's DataLabs Anti-Money Laundering (AML) team. The role involves developing business strategies, managing project delivery, and partnering with various departments to improve compliance and risk management through advanced data methodologies, statistics, and machine learning models. The ideal candidate has a strong quantitative background, experience in developing and validating ML models, and a passion for innovation in the financial services industry.

This role is for a Principal Associate Data Scientist on the Generative AI Systems (Genesis) team within Capital One's Card Data Science division. The team builds state-of-the-art generative AI solutions for various applications including dialogue, text summarization, reading comprehension, speech recognition, image/document processing, and time-series sequencing. The role involves partnering with cross-functional teams to deliver customer-facing and internal applications, leveraging technologies like Python, AWS, and Spark, and building machine learning models through all phases of development. The ideal candidate is customer-focused, innovative, creative, technically proficient, statistically-minded, and adept at handling large datasets.

Senior Distinguished Machine Learning Engineer role focused on technical leadership for productionizing ML applications and systems at scale within the financial services industry. The role involves driving the creation and evolution of ML models and software, leveraging cloud architectures, optimizing data pipelines, and mentoring other engineers. Requires extensive experience in data-intensive solutions, ML development lifecycle, and programming.

Manager of Data Scientists within the Model Risk Office, focusing on validating and building statistical or machine learning models, including those with unique risks associated with Generative AI. The role involves partnering with cross-functional teams, leveraging technologies like Python and AWS, and translating complex work into business goals. The ideal candidate is creative, a leader, statistically-minded, and a data guru.

Lead Data Scientist role focused on developing and deploying deep learning models for underwriting and supporting LLM-based product development in a fintech company.

Senior Manager role focused on Model Risk Office within Capital One, leading teams to identify and quantify risks associated with models, challenge production models, and contribute to model governance. The role involves leveraging data science, machine learning, and various technologies to ensure better decision-making and defend against model failures in a financial services context.

Capital One is seeking a Principal Associate, Data Scientist for their Mainstreet Acquisitions team. This role involves developing and deploying valuation models for credit underwriting, leveraging alternative data sources and advanced modeling techniques. The position requires building machine learning models through all phases of development, from design through training, evaluation, validation, and implementation, using technologies like Python, AWS, and Spark. The ideal candidate is customer-focused, innovative, creative, technically proficient, statistically-minded, and skilled in handling large datasets.

Manager, Data Scientist role focused on Card Intelligence Model Risk Management within Capital One's fintech domain. The role involves building machine learning models through all phases of development, including design, training, evaluation, validation, and implementation. It requires partnering with cross-functional teams and leveraging technologies like Python, AWS, H2O, and Spark. The position emphasizes statistical modeling, data analysis, and understanding customer data to drive data-driven decision-making. Experience in model governance and end-to-end development is preferred.

Manager, Data Scientist focused on Recommendation & Personalization Systems within an Applied AI team. The role involves architecting and deploying personalized recommendation engines using Foundation Models, Reinforcement Learning, and Transformer-based architectures. It operates at the intersection of research and real-world impact, dealing with high-scale ML models and billions of customer records in the fintech domain.

Senior Distinguished Engineer role focused on technical leadership for productionizing machine learning applications and systems at scale within the financial services industry. The role involves driving the creation and evolution of ML models and software, leveraging cloud architectures, optimizing data pipelines, and mentoring engineers. Requires extensive experience in data-intensive solutions and the ML development lifecycle.

This role is in Capital One's Model Risk Office, focusing on identifying and quantifying risks associated with models, including Generative AI. The Senior Associate Data Scientist will build machine learning models to challenge existing production models, contribute to model governance, and validate models across various business domains. They will leverage technologies like PyTorch, Hugging Face, LangChain, Vector Databases, and LLMOps to analyze multi-modal data and present findings to executives.

This role is within Capital One's Model Risk Office, focusing on identifying and quantifying risks associated with models, including Generative AI. The Data Scientist will build machine learning models to challenge existing production models and contribute to the model governance framework. They will validate models across various business domains and present findings to executives. The role requires experience with ML, data analysis, and databases, with a preference for GenAI and model validation experience.

Manager, Data Scientist role at Capital One focused on Emerging Payments & Airkey. The team builds ML models for customer-facing payment experiences, processing large-scale financial data using technologies like XGBoost, transformers, embeddings, and LLMs. The role involves building ML models from design through production for millions of customers, partnering with cross-functional teams, and leveraging various technologies like SQL, Python, AWS, and Spark.

This role focuses on applying AI and ML to HR talent strategy, building models for understanding associate behavior and improving HR efficiency. It involves developing NLP and ML models using prompt engineering, RAG, and evaluation frameworks, leveraging technologies like Python, SQL, AWS, LangChain, Hugging Face, and VectorDBs. The candidate will partner with cross-functional teams to deliver HR tools and AI-powered products, translating complex data science work into business outcomes.

Product Management role focused on AI/ML Model Governance within the Machine Learning Experience (MLX) team at Capital One India. The role involves developing product strategy, understanding needs of data scientists and ML engineers, partnering with leadership, and managing product backlogs for enterprise AI/ML platform products, with a focus on responsible GenAI and ML model deployment.

Staff Applied Scientist focused on architecting and scaling AI guardrails and safety systems for generative models across multimodal platforms (image, video, audio). This role involves data-centric safety, detection, feedback-driven improvements, and translating research into production-ready systems, with a strong emphasis on ML systems architecture and responsible AI deployment.

Senior Machine Learning Engineer focused on building production pipelines and systems to improve deployed generative AI models using user feedback and behavioral signals. The role involves preference modeling, data processing, and evaluation infrastructure for multimodal generative workflows.

Technical Architect role focused on designing and architecting advanced assistant and agentic frameworks using LLMs, VLLMs, and MLLMs, with a specific emphasis on image and multimedia domains. The role involves overseeing technical strategy, collaborating with cross-functional teams, mentoring engineers, and transforming conceptual designs into production-ready solutions. Key responsibilities include defining the vision and roadmap for agent orchestration, tool usage, memory, and scalable evaluation.

Research Scientist role focused on developing and optimizing multimodal guardrail systems for generative AI models (like Adobe Firefly), specifically addressing IP compliance and safety through inference-time alignment, controllable generation, and advanced VLM techniques. The role involves research, experimentation, and collaboration to integrate these safety mechanisms into production-scale systems.

Senior ML Engineer at Adobe Firefly team, focusing on adapting large-scale pretrained multimodal generative models (image, text, video) for creative products. Responsibilities include research, prototyping, integrating new techniques, building end-to-end pipelines, and contributing to data strategy and user workflows. Requires strong ML engineering, deep learning, generative model, and Python skills, with experience in large-scale ML pipelines from training to inference.

Senior Applied Scientist at Adobe Firefly focusing on research and development for large-scale generative AI models for image and video synthesis. The role involves advancing conditional generation and editing techniques, improving model quality and controllability, and developing evaluation frameworks. This position emphasizes pre-training and mid-training of multimodal generative models, with the goal of shipping these innovations into Adobe products for millions of users.

Senior Staff Applied Scientist role at Adobe focusing on transforming AI/ML research breakthroughs into innovative product features for Generative AI, LLMs, and multimodal AI. The role involves scouting, adapting, and improvising research, prototyping, rapid experimentation, and deploying practical innovations for Adobe's products. Responsibilities include developing and enhancing GPU-accelerated pipelines for model training and inference, collaborating with researchers and ML engineers, and publishing work. Requires a Ph.D. or Masters with 10+ years of experience in AI/ML, with expertise in training AI/ML models in multimodal LLMs, Image, or Video, proficiency in training and optimizing large-scale models, and experience with post-training techniques like fine-tuning and alignment.

Senior Staff Machine Learning Engineer at Adobe focused on building and optimizing scalable, high-performance generative AI services and inference pipelines for integration into Adobe products. The role involves designing GenAI services, APIs, and ML workflows for model customization and serving, with a strong emphasis on GPU-accelerated training and inference optimization.

Engineering Manager to lead a team building and operating the agentic AI foundation for Adobe Express, focusing on AI assistants, agentic workflows, and scaling LLM-based features for millions of users. The role requires deep understanding of how LLMs are integrated into complex systems, driving technical direction, and managing end-to-end delivery.

Staff Applied Scientist role focused on Generative AI research and development for visual, audio, and multi-modal outputs. The role involves pioneering research, developing novel generative AI technologies, and training/fine-tuning large foundation models across various modalities. Emphasis on publishing research and collaborating with ML engineers to integrate technologies into Adobe products.

Research Scientist at Adobe Research focusing on generative world models for consistent world representations, long-horizon video and 3D generation, and interactive creative experiences. The role involves inventing algorithms, building prototypes, large-scale training, evaluation, and deployment, with potential integration into Adobe products. Requires a Ph.D. and significant research experience with a strong publication record.

Senior Machine Learning Engineer at Adobe Firefly Gen AI Models and services group, focusing on architecting, optimizing, and deploying generative AI models (image, vector, audio, video, multimodal) for Adobe's creative products. The role involves designing backend services, optimizing model pipelines, and providing technical leadership.

Machine Learning Engineer with 10+ years of experience, including 3+ as a Lead/Architect, to architect and optimize large-scale generative AI model pipelines and backend services for Adobe Firefly. The role involves collaborating with researchers, providing technical leadership, and exploring new ML/MLOps technologies to improve GenAI engineering effectiveness. Requires strong hands-on experience with GenAI models and shipping ML features, with preferred experience in model training/optimization and conversion.

This role focuses on applied research for multimodal foundation models, specifically concerning the scaling, quality, and innovation of training data across image, video, and audio. The Principal Scientist will guide a team in architecture and training strategies, pioneer data ablations, lead research, optimize distributed training pipelines, and translate research into production models for Adobe's creative tools.

Staff ML Engineer/Architect to build LLM-powered agents for personalization and real-time decisioning systems, architecting end-to-end ML systems including feature pipelines, training, and low-latency inference, and leading MLOps practices. This is a 0->1 opportunity to define agentic AI for enterprise personalization.

Senior Machine Learning Engineer to build and operate scalable intelligent AI systems for end-user AI products, focusing on agentic systems including orchestration, tool integration, retrieval, memory, evaluation, safety/guardrails, and high-performance backend systems. The role involves end-to-end architecture ownership, building AI-powered product capabilities, designing agent orchestration, developing core platform components (RAG, memory), establishing safety/governance/MLOps, and providing technical leadership.

Research Scientist role at Adobe focusing on Generative AI, specifically large-scale foundation models and diffusion models. Involves cutting-edge research, development of novel technologies, and potential transfer to products. Requires a Ph.D. and strong publication record in AI/ML.

Machine Learning Engineer at Adobe to build advanced AI platform for creative workflows, focusing on reasoning systems, tool orchestration, and multimodal integrations using LLMs and VLLMs. The role involves post-training and evaluation of LLMs, designing and implementing agent system architectures, and developing practical agents for image generation and editing within flagship products like Photoshop and Lightroom.

Senior Applied Scientist at Adobe focused on improving the quality and controllability of generative multimodal models (images and videos). The role involves designing and implementing end-to-end training pipelines for foundational models, leading core development in pre-training areas, and developing scalable workflows for data curation and distributed training. Collaboration with research, data, evaluation, infrastructure, pre-training, and post-training teams is key to enhancing editing quality, instruction-following, visual fidelity, and edit consistency.

Research Scientist role focused on training large-scale generative AI models for image and video synthesis, emphasizing conditional generation, editing, and improving instruction compliance, controllability, and visual clarity. The role involves collaborating cross-functionally, developing evaluation pipelines, and translating research into production-ready implementations.

Research Scientist role focused on Computer Vision and Machine Learning, with a strong emphasis on developing and deploying solutions that integrate into products. The role involves research initiatives, collaboration with product teams, designing evaluations, generating synthetic data, and manipulating complex datasets. Requires expertise in CV, LLMs, NLP, or multimodal understanding, with publications in top-tier conferences and a track record of production deployment.

Senior Research Scientist at Adobe Speech AI Lab focusing on speech generative AI, audio modeling, and multimodal learning. The role involves leading independent research, designing and advancing state-of-the-art AI models and training procedures, including foundation models and generative systems. Emphasis on modern large-scale model architectures, publishing research, and building prototypes for product integration.

Research Scientist role focused on Generative AI, specifically preparing data, training, fine-tuning, and adapting large foundation models across various modalities (images, video, 3D, LLMs, cross-modal). The role involves pioneering research and development for visual, audio, and multi-modal outputs, deploying new generative AI technologies into Adobe products, and researching novel large-scale foundation models with deep reasoning capabilities. Collaboration with researchers and ML engineers is expected, along with publishing work in scientific venues.

Research scientist role focused on generative AI for visual, audio, and multi-modal outputs. Involves pioneering research, development, and deployment of novel generative AI technologies, including large-scale foundation models with deep reasoning capabilities. Requires expertise in training and fine-tuning models across various modalities and proficiency in deep learning frameworks.

Principal Machine Learning Engineer at Adobe Firefly, leading the development of scalable, high-performance generative AI systems for integration into Adobe products. Responsibilities include architecting and optimizing inference pipelines, building APIs, and providing technical leadership for a team of ML engineers. Requires extensive experience in production-scale GenAI deployments, particularly with training and inference optimization on GPU-intensive systems.

Research Scientist role focused on developing new music generation technology using generative AI, sequence modeling, multi-modal modeling, reinforcement learning, LLMs, diffusion, and distillation techniques. The goal is to push the state of the art and productize research for real-world impact in music creation.

Research Scientist role at Adobe Research focusing on Generative AI, including large-scale foundation models, diffusion models, and multimodal foundation models. The role involves conducting cutting-edge research, developing novel technologies, and transferring them to products. Requires a Ph.D. and strong publication record in AI/ML.

Machine Learning Engineer 4 at Adobe's Firefly Enterprise Video API team, focusing on designing, developing, and deploying GenAI backend services for video. The role involves optimizing model performance, enhancing MLOps, and translating research into scalable ML systems for enterprise customers.

This role is for an AI Software Architect focused on Forward Deployed Engineering for enterprise customers. The individual will own system design, platform standards, and technical relationships with large enterprise clients, transforming their content supply chains with generative AI. Responsibilities include designing end-to-end GenAI systems (RAG pipelines, agent orchestration, API integrations), establishing reusable patterns, shipping production code (minimum 40% hands-on), interfacing with C-level customers, driving product feedback, and mentoring engineers. The role requires experience building and shipping production GenAI products, a deep AI/ML engineering foundation, strong production engineering rigor, and executive communication skills.

Principal Architect to build and implement the AI framework for Adobe Express, merging strong ML skills with proficiency in distributed systems, data architecture, and large-scale service development. This role blends applied research and engineering leadership, focusing on Agentic AI, Create AI, Imaging AI, Motion AI, and Personalization AI, spanning model orchestration, inference systems, data pipelines, caching and storage layers, session analytics, and continuous evaluation frameworks.

Principal Scientist to shape the data strategy for Adobe Firefly's multimodal foundation models (image, video, audio), focusing on sourcing, curation, and training large-scale visual data to improve generative model quality, controllability, and realism for millions of users. This senior IC role involves cross-functional collaboration with research, engineering, and product teams.

Seeking a Sr. Principal Architect to lead the design, build, and evolution of the Adobe Intelligence Platform, an AI infrastructure enabling agentic experiences across Adobe products. The role involves hands-on technical leadership, defining system boundaries, and driving execution for a platform encompassing agentic orchestration, model gateways, knowledge graphs, and planning/reasoning layers at enterprise scale.

Senior Research Engineer role focused on pioneering Generative AI video authoring, inventing and prototyping next-generation creative workflows. The role involves integrating multimodal models into agentic workflows and building user-facing GenAI experiences for creative tools, with a strong emphasis on bridging research and productization.

Senior Data Science Engineer role focused on building and operating production data and AI infrastructure for Adobe's Digital Experience business. The role involves creating LLM-powered agents, customer intelligence products, and reusable platform services, with a strong emphasis on data pipelines, feature workflows, and system reliability. The ideal candidate has deep data engineering experience, GenAI fluency, and platform thinking to ship reliable AI-enabled workflows into production.

This role is for a Senior Machine Learning Architect focused on building and shipping AI-powered user experiences within Adobe Experience Cloud. The architect will design and evolve ML systems that blend GenAI and classical ML techniques, focusing on user-centric data, inference pipelines, and evaluation through user behavior. Responsibilities include end-to-end ownership from data to production, defining evaluation frameworks, and driving system reliability and scalability.

Senior Machine Learning Engineer at Adobe Journey Optimizer B2B, focusing on AI-powered customer journey orchestration. The role involves training and fine-tuning ML models, architecting ML pipelines, and contributing to the deployment and production operations of ML models and systems. Experience with generative AI, LLMs, fine-tuning, and MLOps is required, with a preference for RAG, agentic workflows, and personalization use cases.

Lead the development of next-generation generative AI capabilities for Adobe Creative Cloud, focusing on graphics and vector-based design workflows. This role involves transforming research into scalable, production-ready solutions, driving initiatives from exploration to productization, and impacting millions of creative users.

Director of Product Management to own and lead GenAI Imaging Models roadmap, working with Research, Applied Science, and App teams. Requires strong understanding of generative AI technologies, creator workflows, and experience building GenAI products for creatives. Also requires people management experience.

Director of Product Management to own and lead the GenAI Video Models roadmap, working with Research, Applied Science, and App teams. Requires a strong understanding of generative AI technologies and creator workflows, with experience in building generative AI products for creatives and managing people.

Sr. Manager for Generative AI Data Research at Adobe, leading a team to build multimodal datasets for foundation model training. Focuses on data acquisition, filtering, curation, and pipeline development, with a strong emphasis on system design and applied ML workflows.

Research Scientist role focused on large-scale pre-training and mid-training of multi-modality generative AI models for image and video synthesis, with an emphasis on improving instruction compliance, controllability, and visual clarity. The role involves conducting innovative research, developing sophisticated techniques, collaborating cross-functionally, and translating research into production-ready implementations for Adobe's creative products.

Senior engineer to design and build next-generation AI systems for Adobe Express, focusing on scalable, production-grade AI platforms with agentic experiences. This role involves architecting end-to-end systems for model orchestration, tool integration, memory, inference, data flows, and evaluation.

Senior ML/AI Engineering Manager to lead the Experience ML/AI squad within GenAI Experiences. The role owns the ML strategy for AI Assistant, moving it towards real-time contextual intelligence, predictive workflow understanding, and natural-language UI control across Experience Cloud. Requires setting strategy, operationalizing ML execution, and scaling impact. Focuses on user outcomes and building proactive, grounded intelligence using UI context and user behavior signals.

The ML Services Software Development Engineer will architect and implement performant, robust, and scalable GenAI services supporting deep learning models in large-scale, distributed environments. This role leads inference platform projects, collaborates with ML researchers to optimize GPU utilization, and monitors ML platform performance.

Senior Machine Learning Engineer to design, build, and scale agentic AI platforms and products for enterprise customer experiences and marketing campaigns, focusing on the AEP Agent Orchestrator.

Applied Scientist role focused on developing and fine-tuning large-scale foundation models for video understanding and generation, leveraging state-of-the-art Generative AI technologies. The role involves converting research ideas into production-ready code and collaborating with researchers and engineers.

This role focuses on building and optimizing scalable, high-performance generative AI systems, specifically for inference pipelines and integration into Adobe products. It involves designing and building ML workflows for model customization, serving, and ecosystem integration, with a strong emphasis on GPU-accelerated training and inference.

Machine Learning Engineer at Adobe focused on designing, building, and optimizing backend services for ML and GenAI features, including agentic systems and orchestration. The role involves developing, evaluating, and deploying ML models, taking features from 0 to 1, and integrating solutions into production workflows. Requires strong Python software engineering, experience with production ML systems, and familiarity with cloud platforms.

Lead the development of next-generation generative AI capabilities for Adobe Creative Cloud, focusing on graphics and vector-based design workflows. This role involves transforming research into scalable, production-ready solutions, driving initiatives from exploration to productization, and impacting millions of creative users.

Senior Manager, Machine Learning to lead the Document Cloud AI Team at Adobe. The role involves driving innovation and building transformative document experiences using Gen AI and advanced technology, from concept to customer impact. Responsibilities include leading scientists and engineers, ensuring scalability and reliability, collaborating with stakeholders, fostering a positive team culture, and attracting top talent. Requires strong experience in generative AI, LLMs, ML model development, production deployment, agentic AI systems, MLOps, and cloud ML services.

Research Scientist/Engineer at Adobe focused on image generation/restoration, low-level vision, and image editing for Photoshop, with an eventual posture toward productization. Requires expertise in AI, ML, computer vision, and image processing, with a preference for experience in light transport, image formation, or physically based rendering, and leveraging synthetic 3D scene data.

Senior AI Systems Engineer focused on designing, building, and operationalizing agent-based systems and AI infrastructure to improve developer productivity and engineering workflows within Adobe's Creative Cloud. The role involves developing multi-agent orchestration, building reusable infrastructure, implementing evaluation and observability pipelines, and hardening experimental workflows into production-grade services.

Senior AI Engineering Manager at Adobe, leading a team of Forward Deployed AI Engineers and Creative Pipeline Specialists to build GenAI-powered content production systems for large brands. The role is player-coach, requiring hands-on coding (min 30% time), architecture decisions, and unblocking the team. Responsibilities include owning delivery outcomes, growing the team, setting technical direction, driving product feedback, scaling the organization through reusable capabilities, and representing the org externally. Requires 3+ years of management experience, hands-on GenAI experience (LLM integrations, RAG, agent frameworks), and experience in creative content supply chains. The role focuses on building and deploying AI systems that transform content production workflows.

Sr. Applied Scientist at Adobe focused on improving the quality and controllability of generative multimodal models, specifically in mid-training capabilities for image and video editing. The role involves designing and implementing training pipelines, identifying quality gaps, developing data curation and distributed training workflows, and optimizing inference for production environments.

Senior AI Engineer at Adobe responsible for building and deploying end-to-end AI products, including GenAI applications, LLM-powered agents, and RAG systems. The role involves full lifecycle ownership from ideation with stakeholders to deployment and impact measurement, leveraging AI-assisted coding tools for rapid development on cloud infrastructure.

Senior Manager, Forward Deployed AI Engineer at Adobe, leading a team to build GenAI-powered content production systems for large brands. The role requires a player-coach with a strong technical background, hands-on experience in deploying AI systems (LLM integrations, RAG, agent frameworks), and experience in creative content supply chains. The manager will own delivery outcomes, team performance, and technical quality, contributing at least 30% of their time to technical work.

Machine Learning Engineer focused on building and optimizing scalable generative AI services and inference pipelines for Adobe products. The role involves integrating various generative models, optimizing them for performance, and building APIs for product integration.

Senior Director of Product Management to lead AI and agentic platform capabilities on Adobe Experience Platform (AEP), focusing on core platform services and applications built on top. The role involves defining AI product strategy, leading product vision and roadmap, shaping future agentic AI platform versions, driving cross-functional alignment, and managing a team of product managers. Requires proven platform/infrastructure product leadership, strategic thinking, deep AI/ML background, technical fluency, and experience influencing executive stakeholders.

This role focuses on developing and implementing ML models for search, recommendations, and generative AI use cases within Adobe's creative suite. It involves fine-tuning LLMs and Diffusion models, optimizing inference, and processing multimodal data to assist users and recommend assets. The role also includes research into novel LLM architectures and evaluation methods.

Research Scientist at Adobe's Media and Data Science Research (MDSR) Laboratory, focusing on NLP, Computational Social Science, and ML to develop innovative solutions for future digital experiences. The role involves transforming research into products, building evaluations, generating synthetic data, and integrating ML models into Adobe's platforms. Requires a PhD and production deployment experience, with publications in top conferences.

Machine Learning Engineer role focused on building and maintaining predictive models, optimization algorithms, and Agentic AI solutions for Adobe's advertising platform. The role involves developing production-ready features, working with large datasets and low latency requirements, and managing the full model lifecycle in a scalable production environment.

Senior Machine Learning Engineer focused on building infrastructure for large-scale, multimodal AI training and inference. The role involves developing distributed data loaders, data pipelines, batch inference systems, and improving system performance, scalability, and reliability. It also includes implementing search and retrieval systems, CI/CD workflows, and partnering with researchers to turn model requirements into scalable systems.

Senior Machine Learning Engineer focused on building and implementing AI platforms, leveraging deep learning technologies, and working with large-scale computing frameworks to analyze and leverage data for digital experiences.

Senior Engineer to build AI-native platforms and agentic AI systems that integrate LLMs, recommendation engines, and multi-agent orchestration for personalized digital experiences at Adobe's global scale. The role involves designing, implementing, and prototyping these systems, with a focus on production readiness, evaluation, and responsible AI guardrails. Experience with LLM APIs, multi-agent frameworks, RAG, vector databases, and distributed systems is required.

Machine Learning Engineer to optimize customer experience orchestration by building products that transform audience creation, journey optimization, and personalization. Focus on developing innovative models, designing and deploying applications with predictive and generative models, building autonomous agents, and implementing ML-Ops best practices.

Director of Engineering role focused on leading the development and end-to-end delivery of AI-native, production-ready machine learning products for external clients. Responsibilities include technical and product leadership, team scaling and management, and ensuring excellence in production operations. Requires extensive experience in delivering and managing AI/ML products in production, with strong business and commercial exposure.

Staff Machine Learning Engineer at Adobe to design, build, and maintain AI/ML systems for GenStudio. Responsibilities include framing product features as ML tasks, analyzing trade-offs, managing data labeling, organizing datasets, implementing research techniques, handling cold-start scenarios, defining benchmarks, architecting scalable ML systems, and optimizing model development in GPU/TPU environments. Requires 12+ years of experience, expertise in ML/DL, Python, PyTorch, and scalable AI/ML system design.

Senior Manager, Machine Learning Engineering for Adobe Firefly's GenAI Product Services team. The role involves leading a team to build, deploy, optimize, and scale generative models and APIs for enterprise customers. Responsibilities include technical leadership, strategy definition, roadmap shaping, and cross-functional collaboration. The ideal candidate has strong experience in generative AI, production-scale ML deployments, and engineering leadership.

Machine Learning Engineer & Architect for Adobe Journey Optimizer B2B, focusing on AI and Agents team to define and own ML architecture vision for B2B journey orchestration platform. Role involves training/finetuning models, architecting ML pipelines, recommending models/metrics/governance, providing technical leadership, and deploying/operating ML systems. Requires 10+ years ML experience, 3+ years generative AI, strong Python, deep learning engineering, and experience with post-training techniques.

Machine Learning Engineer at Adobe to optimize customer experience through predictive and generative models, focusing on autonomous agents and agentic frameworks. The role involves designing, developing, and deploying applications, implementing ML-Ops, and collaborating with research and product teams.

Applied Scientist at Adobe focused on transforming research breakthroughs in Generative AI, LLMs, and multimodal AI into innovative product features for millions of users. The role involves scouting, adapting, and improvising the latest research, prototyping, and deploying practical innovations, with a strong emphasis on training and optimizing large-scale models, including post-training techniques and GPU-accelerated pipelines for both training and inference.

This role focuses on engineering GenAI backend services for video, deploying ML models from experimentation to production, optimizing performance, and enhancing MLOps workflows. It requires expertise in Generative Video AI, model optimization, inference efficiency, and GPU acceleration for cloud-scale products.

Senior Customer Facing Applied AI Engineer at Adobe, focused on implementing AI capabilities into customer applications and workflows, analyzing model behavior in production, designing evaluation pipelines, and ensuring AI features are usable, measurable, and scalable. The role involves deep technical work and on-site customer collaboration.

Senior Machine Learning Engineer to build and implement the AI framework for Adobe Express, focusing on Agentic AI, Create AI, Imaging AI, Motion AI, and Personalization AI. This role involves developing and operationalizing end-to-end systems, including LLM orchestration, inference, data pipelines, and evaluation frameworks, with a strong emphasis on distributed systems and large-scale service development.

Forward Deployed AI Engineer responsible for the end-to-end development and launch of GenAI applications using Adobe and third-party generative models. This role involves embedding into customer teams to rapidly prototype, engineer full-stack applications, and bridge field-proven use cases back to the product roadmap. The engineer will also focus on automation, scaling, and documenting best practices.

Senior Engineering Manager to lead teams building and evolving the Adobe Firefly AI Platform, focusing on large-scale model training, fine-tuning, inference, and serving infrastructure for generative AI products. The role involves technical leadership, architectural decisions, and team management to ensure cost efficiency, performance, and reliability.

Machine Learning Engineer role focused on building and optimizing scalable, high-performance generative AI inference pipelines and APIs for integration into Adobe's consumer products. The role involves optimizing models for latency and throughput, productionizing generative models, and developing enterprise-scale systems for customization and serving.

Principal Engineer AI/ML at Adobe, focusing on designing, building, and scaling AI/ML systems for GenStudio. The role involves framing product features as ML tasks, analyzing trade-offs, managing data, implementing research techniques, defining benchmarks, architecting scalable ML systems, and optimizing model deployment. Requires strong software engineering and ML/DL expertise, with experience in Python, PyTorch, and GPU/TPU environments.

This role leads a distributed team focused on Generative AI for Adobe Firefly Foundry, an enterprise-grade managed service. Responsibilities include defining strategy for data acquisition, processing, and quality, enabling multi-modal content generation, and building scalable data, pre-training, and post-training pipelines. The role requires deep understanding of ML data lifecycles, expertise in data quality and governance, and proficiency with cloud technologies, with a focus on ethical AI practices and leading a team through the full ML model lifecycle from research to customer impact.

Director of Software Engineering & Applied AI to lead the development of AI agents, tooling, and automation for customer support, operation, and scaling of Adobe Experience Platform (AEP). Focuses on agentic-first solutions for troubleshooting, proactive monitoring, and adoption acceleration, transforming reactive support into proactive, data-driven customer success operations.

Senior AI Agent Engineer role focused on designing, building, and maintaining intelligent agents for enterprise use cases like customer experience, discovery, support, and lead qualification. Responsibilities include agent development, multi-agent communication, workflow orchestration, lifecycle management, continuous improvement, and deployment. Requires experience with LLM frameworks, conversational agents in production, and cloud platforms.

This role focuses on designing, architecting, and implementing end-to-end GenAI and Agentic solutions for enterprise customers, integrating Adobe's existing platforms with new AI technologies. The Enterprise Architect will act as a technology leader, collaborating with various teams, advising customers, and rapidly prototyping solutions. The role emphasizes translating complex AI concepts into clear strategies and influencing both internal and external communities.

Staff AI VFX Engineer at Adobe's Firefly Foundry, focused on integrating generative AI into high-end visual effects for feature films and episodic content. The role involves building and validating AI-driven VFX workflows, solving production challenges like temporal coherence and art-directable control, owning the integration surface with DCC tools (Nuke, Houdini, Maya, etc.), and implementing multi-modal model orchestration for image, video, animation, and 3D generation models. Requires deep fluency in VFX workflows and working knowledge of generative AI fundamentals, with a focus on shipping production-grade AI-driven assets.

Director of Product Management for Adobe's Firefly Enterprise team, focusing on defining and driving the strategy for training generative AI models using enterprise brand assets. This role involves end-to-end ownership of the custom models experience, including user-facing features, integration into Adobe applications, and extending to new modalities. It requires leadership of a PM team, deep expertise in generative AI and MLOps, and close collaboration with research, engineering, and enterprise customers.

Senior AI Systems Architect role focused on designing and architecting agent-based workflows, data pipelines, and orchestration systems for enterprise applications. This involves translating business needs into scalable AI solutions, defining RAG architecture, authoring technical specifications for LLM-based solutions, and collaborating with ML engineers and product teams.

Senior Director of Product Management to lead the Developer Platform and AI Platform organization at Adobe. This role focuses on architecting internal and external platforms that power AI capabilities, encompassing developer experience, AI coding tools, API design, workload hosting, and the plugin ecosystem. The position requires shipping AI-powered platforms at scale, thinking in systems, and driving the strategy, roadmap, and execution of these foundational AI systems.

Software Engineer role focused on building and deploying end-to-end GenAI applications for enterprise customers. The role involves prototyping, productionizing, and owning the full lifecycle of GenAI solutions, embedding with customers, and contributing to a platform of reusable components. Requires strong full-stack development, hands-on GenAI experience (LLMs, RAG, embeddings, agent frameworks), cloud/DevOps fluency, and customer-facing communication skills.

Director of Product Management to lead the Media Generation product group, owning the product vision, strategy, and roadmap. This role will serve as the product leader across engineering, AI research, design, user research, product marketing, and go to market teams, working with internal teams and external partners to shape joint product experiences and implement the latest models quickly. The role is an opportunity to shape a new, AI-first product at global scale, define the next generation of creative tooling, and work closely with customers.

Senior Software Engineer role focused on architecting and deploying production-grade AI systems, specifically Agentic AI workflows and RAG pipelines. Responsibilities include system architecture, GenAI implementation, model optimization (fine-tuning, prompt engineering), API development, and MLOps. Requires advanced Python, AI frameworks, vector databases, cloud platforms, data engineering, and DevOps skills.

Technical Architect for Adobe Consulting's Brand Concierge Solution, a NextGen Conversational Agent. This hands-on role involves designing, building, and deploying production-grade agentic AI systems, owning end-to-end solution architecture, and leading delivery teams. Responsibilities include prototyping, code review, selecting LLMs and embedding strategies, and managing non-functional requirements like latency and cost optimization.

Senior Staff Product Designer role focused on leading the design and delivery of intelligent agentic systems within creative and enterprise workflows. The role involves building and shipping AI-native capabilities, focusing on AI behavior, orchestration, and adaptive interfaces, with a requirement for direct work with models, prototyping in code, and contributing to production implementations.

Director to lead Multimodal Data Research organization responsible for scaling, quality, and innovation in multimodal training data (image, video, audio) for Adobe Firefly's foundational generative and editing models. The role involves setting vision, leading multiple senior teams, and orchestrating execution across data ingestion, filtering, captioning, generation, editing-centric datasets, and data-driven training experiments.

This role focuses on designing and building AI agents that automate and augment end-to-end workflows, transforming creative and enterprise processes. The engineer will translate business problems into AI-driven solutions, develop ROI models, and prototype/iterate with users, partnering across teams to scale solutions. Experience building AI agents, copilots, or LLM-powered systems, strong systems thinking, and a commercial mindset are key requirements.

Adobe Research is seeking PhD or master's students for an internship to pursue research problems, develop new algorithms, run experiments, and produce prototypes, with the possibility of academic publication and application to Adobe's products. The role involves working with innovative Machine Learning algorithms and web-scale data.

Senior Forward Deployed Engineer role focused on implementing and integrating AI capabilities (specifically LLM-based applications) into customer workflows and applications. This involves building A2A integration patterns, creating SDKs, analyzing model behavior in production, designing evaluation pipelines with metrics and guardrails, instrumenting AI features with observability, and designing/implementing AI-backed services. The role acts as a bridge between customer needs and internal product/engineering, ensuring AI features are usable, measurable, and scalable.

Manager for a team building core systems that support training and development of foundation models for generative AI (image, video, multimodal). Focus on foundational training frameworks, tooling, and codebases for large-scale experimentation, reliable execution, and rapid iteration. Requires strong software engineering, systems experience, and applied ML understanding.

Lead Forward Deployed Engineer at Adobe, focusing on integrating AI capabilities into customer applications and workflows. This role involves implementing A2A integration patterns, creating reusable SDKs, analyzing model behavior in production, designing evaluation pipelines, and instrumenting AI features with observability. The engineer will also design and implement AI-backed services using Python and PyTorch, and act as a bridge between customer needs and internal product/engineering teams to ensure AI features are usable, measurable, and scalable.

Principal Product Manager for Adobe's Agent Orchestrator platform, focusing on security, efficiency, transparency, and user-friendliness of intelligent agents across Adobe Experience Cloud. The role involves defining systems and tools for agent building, evaluation, and deployment, collaborating with engineering, research, and design to balance safety, performance, and developer velocity.

Internship opportunity within Adobe Firefly's applied research organization focusing on AI and generative technologies. The role involves pioneering data, models, applications, and scientific evaluation for images, videos, language, and multimodal models, contributing to both research and product development.

Adobe Research is seeking PhD students for an internship to pursue research problems, develop new algorithms, and produce prototypes, with the possibility of academic publication and application to Adobe's products. The role involves working in areas like AI & Machine Learning, Content Intelligence, and Intelligent Agents.

Principal Service Engineer for Adobe Firefly's Generative AI Services team, leading the development and scaling of GenAI services and APIs. This role involves designing inference infrastructure, providing technical leadership, evaluating MLOps technologies, and driving cross-functional alignment for enterprise-scale GenAI systems powering various Adobe products.

Senior Applied Researcher at Adobe to leverage Generative AI and Machine Learning for customer experience optimization, focusing on audience creation, journey optimization, and personalization. The role involves developing cutting-edge models, building generative AI-powered applications, and providing technical leadership in design, deployment, and operations. Requires a PhD/MS with 10+ years of applied research experience, including deploying models into production, and expertise in LLMs and prompt engineering.

Machine Learning Engineer at Adobe Firefly’s Generative AI Services team, focusing on building and optimizing scalable generative AI systems for integration into Adobe products. Responsibilities include designing inference pipelines, optimizing models, building APIs, and collaborating on model training and serving.

Research Scientist focused on post-training, alignment, and distillation of large-scale generative AI models (image and video generation) for Adobe Firefly. Expertise in RLHF, DPO/GRPO, SFT, and distillation methods is required to improve model quality, efficiency, and safety, with a focus on transferring innovations into products.

Research scientist focused on conditional generation and editing of large multimodal generative AI models (images, videos, audio) for Adobe Firefly. Emphasizes large-scale pre-training and mid-training, with a direct impact on creative workflows for millions of users. Responsibilities include designing and implementing mid-training approaches, owning components like image-to-image editing, building captioning pipelines, supporting VLM finetuning, and developing scalable workflows for data curation and distributed training.

Senior Director of Product Management to lead Firefly Video Studio, an AI-first end-to-end video creation and production environment. The role involves owning product vision, strategy, and roadmap, integrating generative AI with professional creative tools, and leading a cross-functional team.

Seeking a Senior Director of Product Management to lead the product vision, strategy, and roadmap for Adobe's new flagship AI product, 'Graph'. Graph is an AI node editor, a visual, extensible environment where models, tools, and creative intent converge to enable new ways of building with AI for creators, artists, designers, and creative technologists. The role involves defining the product, identifying opportunities, prioritizing features, and driving end-to-end delivery in a matrixed organization, translating complex AI systems into usable product experiences.

Senior Machine Learning Engineer at Adobe Stock's Content Intelligence team, focusing on developing and deploying ML models for content understanding within Adobe's creative ecosystem (Stock, Behance, Firefly). The role involves leading ML model development, collaborating with product and engineering, and mentoring team members, with a strong emphasis on production deployment and innovation.

This role is for a Manager of Applied Research focused on leading and growing a team responsible for training data for Adobe's enterprise generative AI service, Firefly Foundry. The responsibilities include defining and executing strategy for acquiring, processing, curating, annotating, versioning, and ensuring the quality of large-scale datasets, building scalable data pipelines, and collaborating with researchers and ML engineers. The role requires strong leadership, deep understanding of ML data lifecycles for generative models, and expertise in cloud data technologies.

Director of Engineering Program Management focused on AI Platforms and Globalization. This role leads program managers in executing complex, cross-functional localization programs, enabling international product releases. A key focus is improving efficiency and governance through AI-enabled program management practices, embedding AI into core products and internal workflows, and evolving traditional systems into AI-enabled, autonomous, and scalable architectures. The role involves managing a significant outsourcing budget and driving product ownership for Adobe's AI-powered globalization platform.

This role focuses on building agent-based automation and autonomous AI systems, specifically LLM agents and multi-agent orchestration, for data integration and workflow automation within an enterprise customer solutions context. It involves significant data engineering work to prepare and integrate customer data sources with Adobe solutions, leveraging AWS AI/ML and agentic services.

Full-stack engineer to build next-generation AI-first products, integrating AI systems into scalable experiences. Combines UI expertise with full-stack engineering for seamless integration of AI services into Adobe products.

Senior Product Manager for an agentic, AI-first enterprise workflow platform runtime and extensibility foundation. The role focuses on defining the execution model, developer surface area, governance guardrails, and roadmap for production adoption at enterprise scale. Key responsibilities include owning the product strategy for orchestration, execution semantics, state, scaling, reliability, and operability, as well as the end-to-end extensibility platform for custom actions. The role also involves defining agentic runtime primitives and building the trust layer for AI-first execution, ensuring enterprise-grade compliance, auditing, tenancy, and secure execution.

Senior Backend Engineer focused on the inference service for Adobe's Firefly generative AI models. The role involves designing, leading, and optimizing backend services for high performance, latency, and load, with a focus on GPU-based ML inference.

Senior AI Platform Engineer focused on building the foundational infrastructure for AI, analytics, and autonomous agents at scale. The role involves designing and building streaming-first data pipelines, extending the ML Attribute Store with low-latency serving, developing Agent Data APIs and tool servers for autonomous AI agents, and creating an agentic framework for automation and self-healing pipelines. Experience with LLM integration, agentic AI frameworks, and cloud platforms is required.

This role is for a Principal Technical Program Manager focused on Agentic AI within Adobe Express. The primary responsibility is to lead strategic efforts that embed AI into product functionalities and internal development operations, driving efficiency and scalability through AI-enabled workflows, automation, and decision-making. The role involves translating AI capabilities into practical applications, improving team velocity and quality, and championing AI adoption across diverse teams.

The Applied Scientist will work on post-training and distillation of large generative AI models for Adobe Firefly, focusing on improving quality, efficiency, and scalability for image and video generation. Responsibilities include developing distillation pipelines, applying post-training methods like SFT and preference optimization, building tools for data and training workflows, and optimizing models for deployment.

Principal Product Manager for Adobe's Search & Discovery team, focusing on AI-powered agentic search, recommendations, and generative AI for creative tools. The role involves driving product vision, planning, and execution across web, mobile, and desktop products, with a strong emphasis on integrating these AI capabilities to improve creative efficiency. Requires extensive experience in AI/ML product delivery, search technologies, and RAG.

Senior Product Manager to develop an agentic platform strategy, enabling third-party AI integrations and establishing measurement frameworks for AI-native features. The role requires technical strategy to adapt the platform for agentic needs and align leadership on strategy and roadmap.

This role focuses on post-training and distillation of large generative AI models for images and videos, aiming to improve quality, efficiency, and deployability. Responsibilities include developing distillation pipelines, refining post-training methods (SFT, DPO, GRPO, reward-based learning), building infrastructure for training workflows, and optimizing models for deployment efficiency. The role collaborates with researchers and engineers to adapt complex models into efficient production versions.

Senior ML Systems & Efficiency Engineer for Photoshop ART R&D team, focused on optimizing inference performance, latency, and cost efficiency for image editing applications. The role involves deep expertise in AI/ML systems, computer vision, distributed inference, and performance optimization, with a mandate to deliver production-ready ML systems at lower cost and higher efficiency. Responsibilities include designing and optimizing inference systems, developing high-performance GPU kernels, conducting performance profiling, collaborating on distributed serving systems, and establishing cost-aware ML engineering practices.

Lead Engineer role focused on designing, developing, and deploying scalable GenAI solutions, including agents, applications, and microservices. Involves building data workflows, managing API infrastructure, implementing RAG patterns, and optimizing AI performance. Requires strong Python, cloud, and AI/ML infrastructure knowledge.

This role focuses on designing, building, and optimizing AI-powered agents to improve customer experiences with Adobe products. The engineer will own the full lifecycle of these agent systems, from development to continuous improvement, driving business impact through data-driven insights and collaboration.

Machine Learning Engineer at Adobe responsible for developing, implementing, and operating scalable ML models, with a focus on Agentic AI solutions, predictive modeling, Reinforcement Learning, and Forecasting. The role involves end-to-end model lifecycle management, MLOps, performance tuning, production monitoring, and ensuring governance, security, and compliance for ML pipelines.

Senior Applied Machine Learning Engineer to design and deliver intelligent typographic features across Adobe's creative products, simplifying decisions and workflows for millions of users. This role involves applying advanced modeling to design, train, debug, and operationalize ML systems for layout, generative styling, and design intelligence, owning the modeling lifecycle end-to-end and integrating models into hybrid product architectures.

Senior Software Engineer to design and build backend services and APIs for Adobe's Experience League platform, evolving it into a GenAI-first Knowledge Services offering. The role focuses on creating scalable, governed knowledge access patterns for downstream consumers like AI agents and assistants, replacing ad-hoc methods with structured knowledge representations and supporting agentic workflows.

Senior Software Engineer focused on building agentic systems for Adobe Experience Platform's Generative AI capabilities, involving design, implementation, monitoring, and scaling of services that power audience creation, journey optimization, and personalization.

Machine Learning Engineer at Adobe responsible for developing and scaling deep learning algorithms in NLP and computer vision, with experience in RAG and GenAI systems. The role involves building efficient, reusable code and shipping ML-powered products and services.

Senior Machine Learning Services Engineer at Adobe to productionize AI and Generative AI capabilities into Adobe's creative products. The role focuses on building and optimizing backend cloud services for ML inference, including GPU acceleration, quantization, and other optimization techniques. It involves integrating new models, maintaining CI/CD pipelines, and ensuring production standards for observability and reliability.

Director of Product Management for Adobe Brand Concierge, an enterprise GenAI product focused on optimizing customer and business buyer interactions with brands online. The role involves driving product strategy, defining requirements, partnering with engineering and design, engaging with enterprise clients, and representing the product externally. Requires leadership experience in developing net new AI-first offerings and a deep understanding of the Generative AI market.

Principal Product Manager to shape how AI-powered creative workflows integrate with Adobe's collaboration platform, focusing on enabling third-party AI integrations and building next-generation workflow solutions for AI-assisted creative work.

Lead Customer Facing Applied AI Engineer at Adobe responsible for implementing AI integration patterns, creating reusable SDKs, acting as a data analyst for model behavior, designing evaluation pipelines, instrumenting AI features with observability, and designing/implementing AI-backed services. The role involves deep technical work and on-site collaboration with global industry leaders to ensure they extract maximum value from Adobe's AI capabilities.

ML Ops Engineer role focused on operational reliability, scalability, and performance of AI systems, including LLM agents and RAG systems. Responsibilities include managing the model lifecycle, implementing monitoring and observability, developing CI/CD pipelines for AI, automating infrastructure, managing data pipelines, optimizing AI stack performance, incident response, and ensuring compliance. Requires experience in MLOps, DevOps, ML platform engineering, cloud infrastructure, Kubernetes, IaC, ML model serving tools, and Python. Preferred experience with LLM applications, RAG, AI agent orchestration, and vector databases.

This role is for a Principal Engineering Program Manager focused on Generative AI within Adobe's Document Cloud. The primary responsibility is to drive feature development from ideation to implementation by fostering collaboration, managing programs through their full lifecycle, and ensuring smooth execution of GenAI initiatives. The role requires a deep understanding of GenAI core technologies and experience leading complex technical programs.

Director of Machine Learning Engineering to lead a team in evolving a data platform to support AI/ML innovation, focusing on big-data management and compute abstractions within a governed trust framework.

Machine Learning Engineer at Adobe focused on building and scaling data products and AI/ML solutions for enterprise customers, involving the full lifecycle of model development, deployment, and maintenance.

Senior Machine Learning Engineer to design, build, and scale agentic AI platforms and products for enterprise customer experiences and marketing campaigns, focusing on the AEP Agent Orchestrator.

Machine Learning Engineer at Adobe Express AI Foundations to build and scale the core AI platform powering creativity across design, imaging, motion, and personalization. The role involves developing production systems for Agentic AI, Create AI, Imaging AI, Motion AI, and Personalization AI, focusing on model integration, inference services, data pipelines, storage, caching, analytics, and evaluation tooling.

Director of Engineering at Adobe leading a senior engineering organization focused on large-scale, cloud-native platforms and AI/GenAI-powered capabilities. The role involves defining technical vision, leading design and delivery of distributed systems and microservices, and managing teams that build AI/GenAI features and improve engineering efficiency with AI. Requires deep expertise in distributed systems, cloud platforms, and a solid understanding of AI/GenAI.

Product Manager for Adobe's Brands AI system, focusing on enterprise adoption, scaling creative asset production, and ensuring brand consistency and governance. The role involves defining business outcomes, prioritizing use cases, integrating AI into workflows, leading change management, collaborating with technical teams, delivering proof points, measuring value, and scaling adoption across the organization.

This role focuses on building and scaling security controls and governance frameworks for AI/ML and agentic systems within an enterprise. It involves defining policies, implementing technical controls, establishing guardrails, managing access, and performing threat modeling to mitigate risks associated with AI. The role also ensures alignment with regulatory frameworks and supports audits.

Director, Firefly Foundry Growth at Adobe, focusing on driving enterprise adoption of GenAI in creativity, film, and media. This role requires a blend of technical fluency in AI and creative tools, strong business development and partnership skills, and experience in launching or scaling products, particularly within the entertainment and creator ecosystem.

Senior Product Manager for Adobe's Brands AI system, focusing on driving adoption within large enterprises, ensuring brand fidelity and governance, and scaling AI-powered creative asset production. The role involves defining business outcomes, prioritizing use cases, integrating AI into existing workflows, leading change management, and collaborating with technical teams for deployment and value measurement.

Senior AI Artist role focused on creating social media content using generative image and video models, requiring strong visual design skills and proficiency in AI tools like Adobe Firefly. The role involves independently driving creative projects from concept to delivery, selecting appropriate AI models, refining outputs, and evaluating emerging tools.

Seeking an Information Retrieval Engineer to lead the development and optimization of retrieval systems for context-aware large language models (LLMs). This role focuses on building robust Retrieval-Augmented Generation (RAG) pipelines to ensure AI agents and applications have access to relevant information, working at the intersection of data engineering, machine learning, and knowledge management.

Group Product Manager at Adobe to lead AEM Guides, focusing on integrating generative AI and ML into core product experiences for intelligent authoring, automation, content reuse, and improved search/recommendations. The role requires setting product vision, owning the roadmap, and delivering outcomes across growth, adoption, and customer satisfaction, while ensuring responsible AI practices.

Manager for Advanced Analytics and Reporting at Adobe, leading a team to build intelligent tools, reports, dashboards, workflows, and ML/AI pipelines for the Digital Experience business. The role involves technical leadership, people management, and delivering data products focused on customer adoption, retention, and value realization. Responsibilities include overseeing ML/AI workflow design and deployment, predictive models, and LLM-powered agents to automate insights and deliver customer intelligence.

This role focuses on building and scaling intelligent analytics solutions, including predictive models and LLM-powered agents, to drive customer success metrics within Adobe's Customer Solutions organization. It involves data engineering, advanced analytics, and AI/ML model deployment in a production environment.

Director of Data Science & Engineering to build the data foundation, KPI frameworks, and predictive intelligence for Adobe's Experience Platform (AEP) Product Success Engineering team. This role involves leading a multidisciplinary team to architect scalable data systems, develop predictive models, and enable data-driven decision-making, focusing on customer adoption, health, and platform performance.

Internship role focused on applying AI/ML techniques to power next-generation marketing, personalization, and decisioning systems. The role involves building, scaling, and deploying ML systems, including autonomous agents and agentic workflows, and contributing to real-world AI products used by millions. Emphasis on end-to-end lifecycle ownership and operationalizing ML/GenAI.

Software Development Engineer to join a generative AI team, focusing on building generative AI powered tools and AI Agents. The role involves crafting web experiences, promoting design thinking, and using product-driven development for rapid iteration.

Internship role focused on building AI assistants and multi-agent systems for enterprise software, involving research, algorithm development, and evaluation.

This role is for a Senior Product Design Manager at Adobe, focused on leading a team to develop new AI-powered experiences for business professionals within the Document Cloud. The role involves working from early concepts to shipped products, exploring new AI modalities, and collaborating closely with AI researchers and ML engineers to define AI-native ways of working and build user experiences.

Senior Infrastructure Developer to own, evolve, and scale the platform powering demanding ML training and serving workloads. This role involves architecting Kubernetes-native systems, leading cross-geo projects, writing production-grade code (Go, Python, Rust), and ensuring the reliability and efficiency of large-scale GPU clusters. Focus on infrastructure as code, deep observability, and complex networking challenges within a multi-cloud environment.

Director of Product Management for Adobe Firefly Enterprise, focusing on Generative Video and Extensibility (Plugins/APIs). The role involves defining product strategy, leading a team, collaborating with engineering and other product teams, and shaping the integration of Firefly into enterprise workflows and third-party ecosystems. Requires extensive experience in product management leadership, video/media, platform/API development, and enterprise SaaS.

Senior DevOps Engineer specializing in AI Ops to own infrastructure provisioning, CI/CD automation, telemetry pipelines, and production deployment for AI-powered services, agents, and orchestration systems. The role focuses on building and operating infrastructure for reliable, observable, and scalable AI systems in production, with SRE responsibilities for ensuring reliability, resilience, scalability, security, and cost-effectiveness.

Software Development Engineer 5 at Adobe to pioneer semantic enrichment within the Adobe Experience Data Model (XDM), transforming how businesses understand and act on their data by integrating semantic search, knowledge graphs, and advanced natural language understanding (NLU). The role involves crafting intelligent search solutions that incorporate NLU, machine learning, and knowledge graphs to deliver relevant insights, enabling brands to quickly access, understand, and act upon data.

Senior Engineering Manager at Adobe to lead a high-performing engineering team in developing next-generation multi-cloud services, focusing on AI-powered features for customers and internal productivity. The role involves technical leadership, product architecture, roadmap planning, and talent acquisition within the Digital Experience business unit.

This role leads an enterprise function focused on transforming how sales and operations teams use data, analytics, and technology, with an AI-first approach. It involves defining and executing an AI-first analytics ecosystem, modernizing data platforms, and scaling technology operations to drive growth and better decision-making. Key responsibilities include shifting from static reporting to AI-powered decision intelligence, embedding advanced analytics and AI into business workflows, and transforming technology support operations through intelligent automation and conversational AI.

Seeking a Principal Architect to lead the architecture of AI-enabled customer experience platforms, focusing on integrating AI capabilities like RAG, GenAI, and agentic automation into support and sales processes. The role involves defining reference architectures, guardrails, and ensuring alignment across multiple initiatives and teams, with a vendor-agnostic approach.

This role focuses on architecting and designing enterprise solutions that leverage generative and agentic AI, specifically Adobe's Firefly Enterprise Solutions. The architect will lead technical discovery, design scalable solutions integrating AI into customer workflows, build prototypes, and create technical roadmaps. The role also involves developing reusable assets, collaborating with product teams, and staying at the forefront of AI trends to advise customers and shape Adobe's technical positioning. The primary focus is on applying AI to enterprise workflows and content creation at scale.

Director level role focused on defining product vision and strategy for internal employee experience platforms (Workfront, AEM Assets) using AI technologies. The role involves partnering with IT and business leaders, developing metrics, managing a team, and staying up-to-date with AI advancements to incorporate them into product strategy. The goal is to enable, improve, and centralize workflows, enhance employee experience, and promote data excellence.

Backend engineer to enable and accelerate Video APIs powered by machine learning models. Will work closely with ML researchers, bringing AI experiences to users by enabling large-scale productization through cloud-based services. Design and development of services/components, full lifecycle responsibility, collaborate with ML engineers on orchestration and inference workflows, build scalable cloud services with observability, build GPU-optimized model pipelines, work with distributed teams to build GenAI services/API for video workflows, partner with internal client teams and enterprise customers.

This role focuses on building Gen AI-powered concierge experiences for enterprise customers, involving scalable distributed systems, LLMs, RAG, and agentic workflows within Adobe Experience Cloud.

Creative Director for Adobe's in-house agency, focusing on integrating AI into creative work. This role involves developing and executing AI-native creative ideas, shaping content across various formats, and building AI-enabled workflows to increase velocity and scale. The position requires hands-on creative skills, a deep understanding of AI tools as a creative medium, and collaboration with strategy and production teams to define new content models.

Senior Software Engineer to design, build, and scale core GenAI services, evaluation frameworks, and agentic capabilities for Adobe's Experience Cloud. The role involves GenAI platform engineering, developer enablement, and global readiness, with ownership of architecture and cross-team impact.

Full stack engineer for Adobe's Firefly Boards team, focusing on building and scaling an AI-powered mood-boarding and ideation app that leverages multi-modal LLMs to provide a non-linear canvas for creative professionals. The role involves developing innovative user experiences and integrating generative AI capabilities.

Senior Software Engineer for Adobe Express Motion AI team, focusing on building and optimizing scalable software systems for AI features in motion, video, and animation workflows. The role involves integrating generative AI and temporal models into the Adobe Express platform, tackling complex technical challenges in media generation and processing, and collaborating with cross-functional teams to deliver user-facing AI-powered creative tools.

Software Engineer to develop, build, and scale core GenAI services, evaluation frameworks, and agentic capabilities. This role focuses on building shared GenAI core services (Voice, Evaluation, Moderation, AI-powered bug triage) and enabling world-ready GenAI features and agents by embedding internationalization and global quality requirements. The role also involves supporting the modernization and stability of the Continuous Localization (CL) platform and developing CL workflows for LLM-based development.

Senior Technical Consultant for Adobe Workfront, focusing on designing and implementing AI-driven automation and content supply chain solutions for enterprise customers. The role involves integrating Workfront with other enterprise systems, architecting AI-augmented workflows using agentic frameworks, and guiding clients through complex integration needs.

This role is for a Computer Scientist 2 (Frontend) at Adobe, focusing on building new features and experiences for Adobe Express. The role involves full-stack development, including front-end (JavaScript, TypeScript, React), back-end (NodeJS, APIs), and cloud services (AWS). A significant part of the role involves integrating AI capabilities into product features and building agentic workflows for the SDLC, requiring careful design for safety, reliability, and performance.

Full Stack Engineer with expertise in TypeScript, JavaScript, and Web Component Frameworks, responsible for end-to-end feature development, system design, and integrating AI capabilities into product experiences, specifically focusing on building multistage LLM pipelines and AI-powered content generation systems.

Director, Product Marketing for Adobe's ProDesign products, focusing on defining and driving the go-to-market strategy for AI and Agentic products within the creative tooling space. Requires experience launching and scaling AI products, understanding the design industry, and leading cross-functional teams.

This role focuses on architecting and designing generative and agentic AI solutions for enterprise workflows, acting as a technical anchor in the pre-sales process. The Principal Enterprise Solutions Architect will translate GenAI vision into implementable realities, design AI-enabled automation workflows, and contribute to customer-specific technical roadmaps and broader system architectures. The role involves collaborating with internal teams, sales, and customers to ensure successful integration and adoption of AI technologies, particularly Adobe Firefly Enterprise Solutions, within enterprise creative and marketing operations.

Senior Software Engineer to build and maintain image generation, editing, and processing nodes within Adobe's Project Graph, a visual node graph editor for creative workflows. This role involves integrating AI image models, GPU-accelerated operations, and Creative Cloud capabilities into a scalable, distributed system.

Software Engineer to join the Cloud Tooling Development team, designing and building self-service tools and platforms for Cloud and AI enablement. The role involves integrating AI and agentic capabilities into features, abstracting complexity, and enabling cloud/AI access across hyper-scalers and AI platforms. Requires experience with full-stack development, cloud infrastructure, AI stack (LLMs, agents, frameworks like LangGraph), and observability tools.

Senior Director, Product Management for Adobe Illustrator, focusing on defining strategy and roadmap for AI-driven creative workflows and agentic capabilities to drive product growth and user engagement.

This role leads a Digital Accelerator CoE focused on driving AI-first and Agentic AI-led transformation across a global organization. The leader will operationalize the CoE vision by building reusable IP, accelerators, and delivery frameworks to ensure measurable customer value, faster implementations, and improved ROI. Key responsibilities include defining strategy, driving Agentic AI use cases, managing reusable assets, establishing a knowledge platform, standardizing delivery, tracking adoption and business outcomes, leading upskilling initiatives, and partnering with stakeholders.

This role focuses on pre-sales technical engagements for Adobe Firefly and generative AI technologies, helping enterprise customers design and implement creative workflows, integrate APIs, and advise on ethical AI practices. It involves leading GenAI demystification, redesigning production workflows, integrating APIs with enterprise platforms, developing proofs-of-concept, and advising on governance and security.

This role focuses on engaging with and educating the AI community about Adobe's AI initiatives, developing content, fostering relationships with industry experts, and informing internal strategy. The role requires strong communication, technical expertise in AI, and community engagement.

This role focuses on building and maintaining context pipelines for LLMs in an enterprise setting, aiming to improve employee productivity and experience. It involves designing systems that assemble instructions, frameworks, standards, tools, and memory for accurate and safe model responses at scale.

Director of Product role focused on defining and driving product vision for Frame.io, a video collaboration platform. The role emphasizes creating new product experiences in ambiguous, 0->1 environments, leveraging AI as a core building material rather than just a feature. It requires rapid prototyping, customer obsession, and leading product strategy and execution for key product areas, ultimately shipping AI-powered creative collaboration products.

Senior Solution Architect for Adobe Firefly Enterprise Solutions in EMEA, focusing on designing and architecting generative and agentic AI solutions for enterprise workflows. The role involves leading technical discovery, building prototypes, and creating reference architectures to integrate AI into customer creative and marketing processes, acting as a technical anchor in the pre-sales motion.

Software Development Engineer to build cloud services integrating AI/ML and generative AI for Adobe's AEM Sites Optimizer and LLM Optimizer product. The role involves analyzing data, automating hypotheses into self-learning AI-first software, designing prompt engineering strategies, and utilizing RAG.

Senior Application Engineer for Photoshop, focusing on integrating GenAI and AI/ML experiences into the product. This role involves developing and shipping AI-powered features, bridging research prototypes to production, and improving engineering workflows with AI tools. Requires strong C++ development skills, understanding of AI/ML and computer vision, and experience shipping AI-driven features.

This role focuses on building AI/ML solutions and agent coordination systems within Adobe Experience Platform, leveraging LLM and ML technologies for enterprise customers. The engineer will architect, implement, and optimize agent-based systems, focusing on reliability, scalability, and performance, while also contributing to platform development and innovation in agent orchestration.

Senior Software Development Engineer at Adobe in Tokyo, focused on building next-generation digital experiences for the Japanese market by integrating generative AI into Creative Cloud and Document Cloud products. The role involves designing, building, and maintaining software, integrating AI capabilities like text processing and content generation, and prototyping advanced AI techniques such as fine-tuning and RAG for Japan-specific use cases.

Senior Prompt Engineer at Adobe focused on enhancing LLM performance for enterprise use cases, designing multi-step agent workflows, implementing function calling and tool use, and optimizing prompts for accuracy, privacy, and compliance. The role involves collaboration with AI engineers and product teams to integrate prompts into production agent systems.

Senior Information Retrieval Engineer focused on building and deploying scalable RAG pipelines and semantic search systems to power context-aware LLMs for enterprise AI applications. This role involves data processing, ingestion, retrieval optimization, and performance monitoring.

Senior Director of Engineering to lead vision, strategy, and execution of Growth Apps for Customer Experience Services (CES). This role will shape and scale enterprise-grade AI applications, focusing on customer interaction with intelligence-driven interfaces and workflows. The position involves leading a team to build repeatable systems that drive adoption, retention, and expansion at enterprise scale, bridging core platforms and go-to-market motions.

Principal Product Manager to lead the development of commercial AI safety systems, defining strategy and driving execution of frameworks and protections for Adobe's generative AI ecosystem. This role involves collaborating with AI Safety, research, legal, and engineering teams to ensure trustworthiness and commercial viability.

Research Engineer focused on optimizing the resource consumption of large-scale generative AI models for cloud and on-device deployment, bridging cutting-edge research with product development.

Product Manager for AI & Optimization within a programmatic advertising platform, focusing on GenAI and agentic systems for campaign management and optimization. Requires experience in adtech and working with Data Science/Engineering on algorithmic products.

Software Development Engineer to build and launch a new product within Adobe, focusing on a platform for enterprise brands and creators to collaborate on influencer marketing. A core part of the platform will involve Agentic AI systems to streamline workflows, integrating LLM-powered services and processes. The role involves full-stack development, backend services, AI-powered features, and scalable data pipelines.

Software Development Engineer to build and launch a new AI-native platform for enterprise influencer marketing, integrating agentic AI systems and LLM-powered services for workflow automation and optimization.

Tech Lead/Architect to build and launch a new enterprise platform for influencer marketing campaigns, leveraging Agentic AI systems and LLM-powered agents. The role involves defining architecture, ensuring scalability, reliability, and security, and building evaluation frameworks, observability, and trust mechanisms for AI-native systems.

Senior Software Engineer with Python and Generative AI expertise to lead the architecture and deployment of production-grade AI systems, focusing on LLMs, RAG, and Agentic workflows. Responsibilities include building scalable backend systems, implementing GenAI workflows, fine-tuning LLMs, developing APIs, managing data and MLOps, and providing technical leadership.

Senior Software Engineer with Python and Generative AI expertise to lead the architecture and deployment of production-grade AI systems, focusing on LLMs, RAG, and Agentic workflows. Responsibilities include building scalable backend systems, implementing GenAI workflows, fine-tuning LLMs, developing APIs, managing data and MLOps, and providing technical leadership.

Senior Software Engineer with Python and Generative AI expertise to lead the architecture and deployment of production-grade AI systems, focusing on LLMs, RAG, and Agentic workflows. Responsibilities include building scalable backend systems, implementing GenAI workflows, fine-tuning LLMs, developing APIs, managing data and MLOps, and providing technical leadership.

This internship focuses on building LLM-powered solutions for marketing efficiency using generative AI, agentic workflows, and RAG. The role involves designing, developing, and integrating these AI systems into marketing applications, collaborating with cross-functional teams, and staying updated on LLM trends. Requires experience with RAG, autonomous workflows, and multi-agent systems.

Senior Software Engineer to build and evolve the platform foundation for Adobe web applications, focusing on developer experience through intelligent tooling and AI-enabled systems. The role involves improving build systems, CI/CD, and introducing AI-assisted capabilities for code generation, testing, and debugging.

Director of Product Management to lead typography into the era of generative and AI-assisted design. This role will define the product vision for typography integrated with Adobe Firefly and Creative Cloud, lead a team of Product Managers, and champion creators by balancing AI assistance with typographic quality and user intent.

Principal Product Manager for Enterprise-focused generative AI, focusing on multimodal models (imaging, video, audio) for content production. Responsibilities include strategy, roadmap, customer engagement, and translating research into production-ready solutions with a focus on quality, customization, and governance.

Software Development Engineer to join an innovative team at Adobe, focusing on crafting new generative AI powered tools for productivity and collaboration. The role involves addressing complex design obstacles, building reusable and scalable code, and driving product-driven development for rapid iteration and measurable impact. Experience with generative AI applications, especially AI Agents, is required.

This role is for a Principal Strategic Program Manager at Adobe, focusing on leading and orchestrating large-scale Generative AI programs. The role involves defining strategy, roadmaps, and execution for AI initiatives, including model development, infrastructure, safety, evaluation, and product integration. It requires deep understanding of AI/ML systems and experience in enterprise-grade environments with security and compliance requirements.

Engineering Manager for Adobe Express in Bucharest, Romania, responsible for leading a team of engineers developing AI/ML-powered features and driving AI adoption across teams. The role involves managing feature development, collaborating with cross-functional teams, determining technical requirements, and promoting innovation. Key responsibilities include hands-on AI/ML experience, driving AI adoption beyond a single team, establishing success metrics, and contributing to governance practices for safe and scalable AI usage.

Senior Engineering Manager for Adobe Firefly, leading a team to deliver AI-powered creative experiences, focusing on product innovation, generative AI integration, and commercialization. The role involves driving end-to-end product execution, defining roadmap priorities, owning technical strategy for AI capabilities, and ensuring performance, scalability, and reliability.

This role focuses on the end-to-end development and launch of GenAI applications by integrating Adobe and third-party generative models. The engineer will embed with customer teams to build proof points rapidly, co-develop features, and bridge field-proven use cases back to the product roadmap. The role involves full-stack development, rapid prototyping, and scaling solutions with CI/CD pipelines and governance checks.

Product Security Engineer at Adobe focused on testing AI/ML and LLM-powered products. Responsibilities include reviewing AI-related penetration testing and bug bounty submissions, defining AI testing scope, driving resolution of security issues, building Security Testing reports, and communicating with external researchers. Requires strong application security knowledge, LLM testing methodologies, and hands-on experience in penetration testing AI/ML products.

AI Product Manager role focused on co-innovating and launching generative AI solutions with enterprise customers, bridging customer needs with product strategy and engineering.

Senior Software Engineer to build the platform powering Adobe Experience Platform's Generative AI capabilities, focusing on audience creation, journey optimization, and personalization at scale. The role involves architecting, designing, and building highly available, scalable services with comprehensive monitoring and alerting, working in multi-functional teams within the ML space.

This role involves building and shipping features and integrations for enterprise customers, with a focus on experimenting with Generative AI and agentic workflows to create novel demos and automation tools. The engineer will write production-grade Java/Scala code, troubleshoot integration issues, and collaborate with architects and product teams. Familiarity with LLM development, prompt engineering, and agentic frameworks like LangChain is required, with RAG knowledge being a plus.

Software Developer Engineer 4 at Adobe to join the team building Adobe’s next-generation AI-first marketing application. This platform is redefining customer engagement workflows with speed, agility, and full-stack productivity for modern marketers. The role involves developing and deploying critical components of a new Agentic App, translating product goals into engineering tasks, evaluating tools, writing clean code, and collaborating cross-functionally. Requires 4-6 years of experience, strong CS fundamentals, expertise in Java/Scala, and familiarity with cloud-native architectures and CI/CD. Experience with Campaign Execution systems and Generative AI is a plus.

Senior Director of Product Management for Adobe's Experience Manager Sites and Forms, focusing on personalization at scale and leading the product strategy for Brand Concierge, a conversational brand ambassador. The role involves evolving product strategy, ensuring technical execution, collaborating with other product teams, and establishing customer and partner relationships. Requires deep product management expertise, innovative thinking, understanding of generative AI and content delivery, and a record of implementing AI/ML capabilities, preferably in creative or marketing tooling.

Product Manager role focused on building Agentic AI workflows for Adobe's Go-To-Market (GTM) and Sales teams. This involves defining product vision and strategy for Planning Agents, Campaign Orchestration Agents, and Seller Productivity AI Assistants. The role requires experience with LLM and agentic architectures, prompt design, RAG, tool calling, and evaluation, with a strong emphasis on a builder mentality and delivering zero-to-one products.

Senior Director of Engineering for Mixed Media Authoring at Adobe Express, leading the engineering vision and execution for combining text, images, graphics, motion, and generative AI into multimedia content. The role involves advancing core authoring capabilities, embedding AI innovation, and scaling a world-class engineering organization to deliver intuitive tools, resilient platforms, and new creative possibilities for millions of creators worldwide.

Senior Software Engineer role focused on architecting and scaling distributed systems for Adobe's Real-Time Customer Data Platform (RTCDP). The role involves integrating Generative AI/ML for personalization, building low-latency data pipelines, and developing cloud-native microservices. Emphasis on real-time data processing, identity resolution, and customer profiles at massive scale.

Senior Software Development Engineer to join the Adobe Agent Orchestrator Platform team in Bucharest. The role focuses on engineering reusable components, optimizing agent workflows, and ensuring real-world performance in production environments for agentic AI systems. Responsibilities include designing and developing the next generation of the platform, architecting agent coordination systems, and innovating in agent orchestration and distributed coordination.

Senior Staff Engineer to lead the Agent Platform for Firefly Boards, an AI-powered creative app. This role owns the production-grade engineering systems for the server-side agent runtime, integration with the central agent platform, and the application stack enabling real-time agent actions on an infinite canvas. Responsibilities include state management, checkpointing, error recovery, observability for long-running operations, defining the browser/server execution boundary for agent tools, and integrating with Adobe's central agent platform. The role also involves refactoring APIs for agent consumption and ensuring production-grade systems concerns like observability and latency budgets. This is a senior IC role focused on engineering direction and cross-organizational partnerships.

Engineering Manager (AI/ML) at Adobe leading a team focused on building next-generation AI-enabled audio & video editing solutions. The role involves people management, technical strategy, and hands-on experience integrating AI/ML into production software for consumer-facing desktop applications.

Lead Product Management for Firefly Boards, a collaborative AI-first creative workspace for ideation, planning, and alignment. This role defines product vision, strategy, and roadmap, integrating AI generation and organization tools into creative workflows and connecting with downstream Adobe tools.

Director of Product Design for Adobe GenStudio, focusing on defining and expanding GenAI-powered creative, marketing, and automation workflows for enterprise customers. The role involves leading a design team, driving strategy, and collaborating with research, product, and engineering executives to create end-to-end experiences.

Research Scientist roles at OpenAI focusing on developing innovative machine learning techniques and advancing the research agenda, with a focus on discovering generalizable ideas and contributing to a broad research vision. The role emphasizes owning a research agenda and pursuing long-running projects.

Research Engineer/Scientist focused on advancing AI alignment and capabilities using cutting-edge reinforcement learning methods to train intelligent, aligned, and general-purpose agents. The role involves pushing the boundaries of RL research, building next-generation generative models, and deploying them at scale, with a focus on core reasoning paradigms and innovations.

Research Engineer focused on building environments and methodologies for measuring and steering frontier AI models towards safe AGI/ASI, influencing training and launch decisions.

OpenAI is seeking a Distributed Training Engineer for their Sora team to improve training throughput for video models. This role involves optimizing the internal training framework, collaborating with researchers, and ensuring hardware efficiency for supercomputer training runs.

Researcher focused on developing and scaling new LLM architectures to improve intelligence and efficiency, with contributions to training and inference infrastructure. Requires deep understanding of LLM architectures and an empirical approach.

Researcher focused on studying internal representations of deep learning models to understand model behavior and engineer more understandable representations, with a focus on AI safety and ensuring the safety of powerful AI systems. The role involves developing and publishing research, engineering infrastructure for studying model internals, and collaborating across teams.

OpenAI is seeking a Research Engineer for the Frontier Evals team, focusing on building evaluations for AI models in the finance domain. The role involves identifying crucial financial capabilities, designing quantification methods, owning a research agenda for evaluation development, and refining frontier model assessments. This position is critical for steering AI progress towards safe AGI/ASI.

Research Scientist role focused on developing novel reinforcement learning techniques using synthetic data, environments, and feedback to train and evaluate frontier AI models, with a focus on generalization and alignment. The role involves designing experiments, analyzing training dynamics, and integrating research into production pipelines.

Research Engineer/Scientist focused on developing and optimizing on-device transformer models, including multimodal capabilities, for future computing devices. The role involves training and evaluating models, developing novel architectures, and translating research into practical applications, with a focus on performance optimization and rigorous scientific methodology.

Researcher focused on mitigating loss of control risk in frontier AI models, designing and implementing an end-to-end mitigation stack for preventing, monitoring, detecting, containing, and enforcing against intentionally subversive or insufficiently controllable model behavior. This involves integrating safeguards across products and research, evaluating technical trade-offs, collaborating with risk modeling and evaluations teams, and executing rigorous testing and red-teaming workflows against advanced AI behaviors like sandbagging, monitor evasion, exploit-seeking, unsafe tool use, or strategic deception.

Researcher focused on identifying, quantifying, and understanding future AGI misalignment risks. The role involves designing worst-case demonstrations, developing adversarial and system-level evaluations, creating automated red-teaming infrastructure, researching alignment technique failure modes, and publishing findings to influence safety strategy and product safeguards.

Research Engineer role focused on deploying and optimizing advanced ML models into production, transforming research into real-world applications. Involves collaboration, scaling data pipelines, and ensuring model performance and maintenance.

Software Engineer focused on optimizing large AI models for high-volume, low-latency, and high-availability production and research environments. This role involves working with researchers and engineers to bring AI technologies into production, improving the inference stack's performance, and optimizing hardware utilization.

Research Engineer/Scientist focused on post-training of pre-trained models for deployment in products like ChatGPT and API. The role involves owning a research agenda to improve model capability and performance, collaborating with other teams, building robust evaluations, and implementing/debugging code. Requires strong ML engineering skills, research experience, and understanding of machine learning applications and model evaluations.

This role focuses on building and optimizing high-performance inference systems for large-scale AI models, translating research ideas into efficient and scalable inference infrastructure. It involves owning core execution paths, distributed inference across multiple GPUs, and optimizing operators and kernels, with a strong emphasis on performance, correctness, and realism for research enablement.

Machine Learning Engineer on the Integrity team at OpenAI, focused on defending against adversarial threats and misuse of AI platforms. The role involves designing, deploying, and optimizing ML models for content understanding and abuse prevention, working with researchers and engineers to turn research into tangible solutions, and ensuring the trust and safety of the platform.

OpenAI's Integrity team, within Applied Engineering, is seeking an experienced Engineering Manager (Web Safety) to lead a team of senior Machine Learning Engineers. The role involves architecting and building next-generation system protections, directly contributing through hands-on design, model training, and deployment strategies. The team uses state-of-the-art models to detect and prevent problematic content, establishing robust evaluation frameworks and metrics. The role also includes managing and mentoring the team, and collaborating with Research, Safety, Product, and Policy teams.

OpenAI is seeking a GPU Inference Engineer to optimize model serving efficiency, inference performance, and scalability for their multimodal foundation models, Sora. The role involves kernel-level systems, data movement, and low-level performance tuning to support the growth and reliability of AI systems.

Software Engineer focused on building and optimizing inference infrastructure for OpenAI's multimodal models (image, audio) at scale, ensuring high-throughput, low-latency delivery and enabling research to production workflows.

This role focuses on measuring and accelerating product-market fit for AI developer tools, specifically within the Codex product team at OpenAI. The Data Scientist will define developer productivity metrics, design and interpret A/B tests for new coding models and features, and analyze model performance across various languages and tasks. The insights generated will directly influence the product's direction and the broader software engineering industry.

Software Engineer focused on scaling and optimizing OpenAI's inference infrastructure on emerging GPU platforms, specifically AMD accelerators. The role involves working across the stack from low-level kernel performance to high-level distributed execution, integrating internal model-serving infrastructure, debugging distributed inference workloads, and collaborating on high-performance GPU kernels and communication libraries.

Machine Learning Engineer focused on designing and scaling distributed data infrastructure for large-scale multimodal training and evaluation in robotics, ensuring reliability and efficiency for rapid iteration cycles.

Research Engineer role focused on designing, building, and optimizing state-of-the-art speech models (speech-to-speech, transcribing, text to speech) and transforming research breakthroughs into tangible OpenAI speech products. Involves collaboration with cross-functional teams, implementing scalable data pipelines, and ensuring models are production-ready.

Lead the implementation of the low-level inference stack for on-device transformer models, including kernel development and runtime systems, while collaborating with researchers and hardware vendors to optimize model architectures for deployment constraints.

This role focuses on improving the performance, reliability, and usefulness of AI agents, specifically for software engineering tasks. It involves designing agent behaviors, developing evaluation metrics, optimizing through prompting and tool-use, analyzing production failures, and building feedback loops to enhance models and agent capabilities. The goal is to bridge the gap between research potential and real-world application, ensuring agents are dependable tools.

Machine Learning Engineer to build and improve AI systems for strategic partners adapting OpenAI models to cloud-native environments. This role involves post-training workflows, evaluation, data pipelines, model behavior, and API/infrastructure integration, focusing on customizing and deploying models safely and reliably.

Researcher focused on post-training agentic models, developing horizontal improvements for factuality, instruction following, tool use, and multi-agent collaboration. The role involves building and improving training/evaluation infrastructure and creating evals to ensure models are ready for shipment, directly impacting models used by millions.

Software Engineer focused on optimizing inference performance across application, model, and fleet layers. This role involves building performance models, analyzing inference workloads, enhancing tooling for bottleneck identification, and collaborating with teams to implement improvements and project future needs. The core of the role is to drive faster and cheaper inference.

Research Engineer role at OpenAI focused on building AI systems with unprecedented performance, requiring strong engineering skills in massive-scale distributed ML systems and algorithm science. The role emphasizes building and advancing AI capabilities.

Research Engineer focused on retrieval and search algorithms and methodologies for production deployment in API and ChatGPT, involving novel research and collaboration with cross-functional teams. Requires experience in production ML systems, vector databases, and internet-scale search.

Researcher focused on AI safety, specifically in training models for robustness, alignment, and adversarial resistance using techniques like RLHF. The role involves setting research directions and implementing improvements in OpenAI's products.

This role focuses on improving the core distributed machine-learning training runtime for OpenAI, aiming to accelerate researchers and enable frontier-scale model runs. The engineer will work on high-performance data movement, fault-tolerant training frameworks, and distributed process management to increase both training throughput and researcher throughput.

Software Engineer focused on the collective communication stack for large-scale AI model training, using C++ and CUDA to optimize network performance on custom supercomputers. This role directly supports the training of OpenAI's flagship models and collaborates with ML researchers.

Software Engineer role focused on building and scaling the infrastructure for training and deploying AI agents, including a novel container orchestration platform and production deployment systems. Collaborates with researchers and product teams to enable complex agentic models and launch agentic products.

Manager for a Forward Deployed Engineering team at OpenAI, responsible for leading a team that turns research breakthroughs into production systems for customers. The role involves owning end-to-end delivery outcomes, informing product and research roadmaps, and ensuring safe deployment at scale. Requires strong leadership, technical delivery experience, and the ability to make sound decisions under pressure.

Research role focused on ensuring AI systems are safe, trustworthy, and aligned with human values, developing methodologies for robust intent following, and integrating human oversight.

Researcher focused on AI safety and societal impacts, translating policy problems into technical research, building methods for public input into model values, and increasing rigor of external assurances for AI model deployments.

Researcher focused on AI safety, specifically developing methods for oversight of frontier AI models, identifying and mitigating misuse and misalignment, and improving models' reasoning about human values. The role involves developing AI monitor models, designing red-teaming pipelines, and collaborating with cross-functional teams.

Researcher focused on AI safety and alignment techniques for healthcare applications, aiming to improve model behavior, knowledge, and reasoning, and integrate these methods into core training and product launches.

This role focuses on leading end-to-end deployments of frontier AI models for strategic customers, bridging customer needs with core platform development. The FDE will own the entire delivery lifecycle, from discovery and scoping to system design, build, and production rollout, ensuring measurable workflow impact and gathering feedback to influence product and model roadmaps. The role involves building full-stack systems, embedding with customer teams, and contributing code directly when necessary, with a strong emphasis on making trade-offs between scope, speed, and quality.

This role focuses on leading end-to-end deployments of frontier AI models for strategic customers, building full-stack systems, and driving production adoption. It involves technical scoping, system design, build, and rollout, with a strong emphasis on customer value and feedback loops to improve product and model roadmaps. The role requires contributing code, codifying patterns, and sharing field insights.

This role focuses on leading end-to-end deployments of frontier AI models for strategic customers, involving technical scoping, system design, build, and production rollout. The engineer will partner closely with customer teams, contribute code, and codify working patterns into reusable tools. Success is measured by production adoption, workflow impact, and feedback that influences product and model roadmaps. The role requires experience in building or deploying LLM-powered systems and delivering complex systems in ambiguous environments.

This role focuses on deploying frontier AI models into production systems for strategic customers, involving end-to-end ownership from discovery and scoping to system design, build, and rollout. The engineer will partner with customer teams, contribute code, build full-stack systems, and provide feedback to improve models and product roadmaps, measuring success through adoption and impact.

This role focuses on leading end-to-end deployments of frontier AI models for strategic customers, involving system design, build, and production rollout. The engineer will work closely with customer teams to deliver value, gather feedback for product and model improvements, and contribute to the development of reusable tools and playbooks. The role requires strong engineering experience, including building and deploying LLM-powered systems, and the ability to manage complex projects in ambiguous environments.

Software Engineer focused on optimizing low-level software for AI accelerators to improve efficiency and performance for large-scale training and inference of AI models, including LLMs and recommender systems.

Research role focused on embedding retrieval and agentic search, developing foundational technology for future frontier models. Involves designing new embedding training objectives, scalable vector store architectures, and dynamic indexing methods, with potential for publication and integration into OpenAI products.

Engineering Manager to lead a team responsible for delivering innovative multimodal API products, including real-time processing, speech transcription, speech generation, and image creation. The role involves owning the product roadmap, collaborating with research teams, and guiding technical decisions for scalability and robustness.

Research Engineer focused on integrating privacy into AI systems, developing and deploying privacy-preserving ML algorithms, measuring robustness against privacy attacks, and defining privacy standards for the ML lifecycle.

Research Engineer role focused on building and improving AI systems for code generation, reasoning, and agentic behavior. The role involves research, experimentation, system optimization, and deployment across the full lifecycle of coding capabilities, aiming to enhance products like ChatGPT and the API.

This role is a Technical Lead for Safety Research at OpenAI, focusing on advancing AI safety and alignment. The team works on implementing robust, safe behavior in AI models, developing new evaluations for misalignment, and supporting human oversight. The lead will set research directions, drive exploratory research, and collaborate across teams to ensure strong safety results. Key responsibilities include setting research strategies, coordinating with cross-functional teams, evaluating model safety, and conducting research on topics like RLHF, adversarial training, and robustness. The role requires a strong track record in AI safety research, leadership experience, and a deep understanding of deep learning.

The Training Performance Engineer will drive efficiency improvements across OpenAI's distributed training stack, focusing on optimizing GPU utilization, throughput, and uptime for large-scale distributed model training. This role involves profiling, analyzing performance bottlenecks in compute, communication, and storage, and collaborating with engineers to improve kernel efficiency, scheduling, and collective communication performance, particularly for pre-training.

Research role focused on intent alignment for AI models, including instruction following, honesty, calibration, and robustness. Involves designing and running experiments, training models with RL, developing evaluations for failure modes, and integrating successful techniques into model development. Aims to produce publishable research and deployable techniques.

Researcher focused on pretraining safety for AI models, developing upstream safety evaluations, creating safer priors through targeted pretraining, and designing safe-by-design architectures. The role involves identifying safety-relevant behaviors in early-stage models and reducing risk during training.

Software Engineer role focused on building and optimizing the low-level stack for AI supercomputing clusters, including runtimes, kernels, and compiler infrastructure, to orchestrate computation and data movement for distributed training workloads.

Principal-level Offensive Security Engineer focused on deep, hands-on penetration testing of OpenAI’s agent-powered products, infrastructure, and model-integrated application surfaces. Assesses complex systems, identifies vulnerabilities, validates exploitability, and partners with engineering teams to drive fixes. Builds tools and automation for offensive security workflows.

Software Engineer to design and scale infrastructure for large-scale multimodal training and evaluation in robotics at OpenAI. Focus on distributed data pipelines, ML infrastructure, and ensuring scalability and reliability.

This role focuses on helping customers adopt OpenAI's coding tools (Codex) by acting as a technical partner, guiding engineering teams in integrating Codex into their projects and workflows. The engineer will design, validate, and scale AI workflows, build demos and integrations, lead workshops, and contribute technical content. The role blends technical architecture, product strategy, and customer-facing leadership, aiming to accelerate the deployment of intelligent coding systems.

This role focuses on identifying, modeling, and forecasting risks from frontier AI systems, ensuring evaluation frameworks and safeguards are robust. It involves developing threat models for misuse and alignment risks, forecasting future risks, and connecting technical, governance, and policy perspectives on AI safety and preparedness.

Research Engineer focused on hardware-silicon co-design for AI workloads, optimizing numerics, architecture, and technology bets. Involves debugging performance gaps, writing quantization kernels, evaluating numerics via model evals, and prototyping RTL for novel numeric modules. Aims to bridge ML research and hardware development for OpenAI's supercomputing infrastructure.

Researcher focused on identifying, tracking, and preparing for catastrophic risks related to frontier AI models, with a specific emphasis on biological, chemical, and cyber risks. The role involves designing and building evaluations for frontier AI models, contributing to risk management strategies, and ensuring the scientific validity of preparedness capability evaluations.

Software Engineer on the Platform Systems team at OpenAI, responsible for designing and building distributed systems for failure detection, tracing, and observability in large-scale AI training jobs. This role focuses on operating and improving the reliability and performance of OpenAI's training infrastructure.

Manager for Forward Deployed Engineering team responsible for partnering with customers to turn research breakthroughs into production systems using frontier models. The role involves leading and growing a team, owning end-to-end delivery outcomes, and ensuring fieldwork informs roadmap priorities and supports safe deployment at scale. Requires strong leadership, technical project management, and experience with production-grade code.

Researcher focused on identifying and mitigating cybersecurity risks associated with frontier AI models, designing and implementing an end-to-end mitigation stack for prevention, monitoring, detection, and enforcement.

This role leads the Automated Red Teaming (ART) effort, focusing on building scalable, research-driven systems to uncover failure modes in AI models and safeguards. The goal is to translate these findings into actionable improvements and reduce expected harm by identifying weaknesses early and reliably. The role involves research into automated classifier jailbreak discovery, bio threat-development elicitation, and CoT monitoring evasion probing, with a strong emphasis on applied research, evaluations, and building scalable automation.

Product Manager for OpenAI's API Agents team, focusing on defining and guiding the future of agentic applications built on OpenAI's models. The role involves understanding developer needs, setting roadmap priorities, and collaborating with research and engineering to deliver developer products and features like SDKs and APIs.

This role is for a Research Infrastructure Engineer focused on ML training systems at OpenAI. The engineer will build and maintain the infrastructure that enables novel research ideas for large-scale model training, improving reliability, debuggability, and performance. The work involves debugging across various systems (Python, PyTorch, distributed systems, GPUs, networking, storage) and designing APIs for complex training workflows.

Manager for AI Deployment Engineering focused on the Codex product, responsible for leading a team that helps customers integrate and scale AI coding tools into their software development lifecycle, ensuring reliable and secure adoption.

Lead security research on AI systems, focusing on vulnerability discovery, validation, and remediation using AI agents. This role involves building AI-driven systems, improving model capabilities, and contributing to the Codex Security product line.

This role focuses on leading end-to-end deployments of frontier AI models for strategic customers, building full-stack systems, and driving production adoption. It involves technical scoping, system design, build, and rollout, with a strong emphasis on customer collaboration and using evaluation feedback to influence product and model roadmaps. The role requires contributing code, codifying patterns, and sharing field insights.

Research Engineer/Scientist focused on RLHF and post-training for personalized, multimodal AI systems within the Consumer Devices group. The role involves building learning and evaluation foundations for adaptive models, working on reward modeling, preference learning, and long-horizon evaluation to improve model behavior in realistic user settings, with a strong product grounding.

Software Engineer focused on building and operating the production infrastructure for Codex agents, including sandboxed execution, orchestration, stateful workflows, and optimizing performance (tokens, latency, reliability, cost) for a fleet of AI agents.

AI Deployment Engineer focused on working with strategic startup customers to optimize their AI systems, prototype prompts/agents, and translate customer feedback into reproducible evaluations and product improvements for OpenAI's research and products. The role involves deep technical engagement, understanding system behavior, and building relationships within the startup ecosystem.

Forward Deployed Engineers (FDEs) lead complex end-to-end deployments of frontier models in production alongside strategic customers. This role involves discovery, technical scoping, system design, build, and production rollout, partnering directly with customer engineering and domain teams. Success is measured by production adoption, workflow impact, and feedback that influences product and model roadmaps. The FDE will contribute to both customer delivery and core platform development, working closely with various internal teams and potentially contributing code directly. The role requires strong engineering and deployment experience, particularly with LLMs or generative models, and the ability to manage complex systems in ambiguous environments.

This role is a founding Technical Deployment Lead at OpenAI, focused on partnering with customers to deliver complex AI systems. The role involves defining delivery processes, translating business needs into technical plans, managing execution across engineering and research teams, and ensuring customer adoption and value realization. It requires deep technical project management, ownership, and the ability to work in ambiguous, high-autonomy environments, with a focus on shipping AI/LLM systems to customers and codifying reusable patterns from field insights.

Researcher focused on designing and building privacy-preserving safety systems for frontier AI models, involving auditable mechanisms for harm detection and mitigation while preserving user data privacy. The role aims to scale automated safety systems to minimize human review and address frontier risks.

Software Engineer focused on building and scaling retrieval systems for agentic search, enabling models to retrieve and act on information. This role involves designing and operating indexing systems, retrieval pipelines, and serving layers, with a focus on performance, reliability, and observability at scale. It supports retrieval across OpenAI products and research, integrating with pretraining, inference, and product teams.

AI Deployment Engineer focused on helping customers adopt OpenAI's coding tools (Codex) by guiding them in integrating Codex into their projects and workflows, designing and validating advanced AI workflows, and building demos and integrations. The role involves technical consulting, customer-facing leadership, and contributing to product strategy.

Manager for Forward Deployed Engineering team responsible for partnering with customers to turn research breakthroughs into production systems, owning end-to-end delivery outcomes, and informing roadmap priorities through fieldwork. Requires experience managing customer-facing engineers and leading high-pressure technical projects.

Researcher focused on studying and shaping aligned behavior in frontier AI models through various training stages (pre-training, mid-training, post-training). The role involves developing synthetic data methods, building evaluation loops, designing data generation pipelines, and creating experiments to distinguish durable learned behavior from artifacts. Collaboration with other teams is key to translate research insights into better model behavior.

The role focuses on optimizing the performance and cost of AI systems, specifically the Codex agents, which involve LLM inference, cloud orchestration, and agentic work management. The engineer will hunt down inefficiencies, build tooling for measurement and profiling, and collaborate to improve latency and cost.

AI Deployment Engineer role focused on working with strategic startup customers to optimize AI systems, identify failure modes, and translate learnings into product improvements and evaluation systems. This role involves prototyping prompts and agents, designing evaluations, and acting as a technical partner to customers.

The Data Scientist, Safety Systems role focuses on establishing a data-driven approach to understand, evaluate, and monitor the safety of production AI systems. This involves defining and implementing metrics, creating dashboards, and collaborating with researchers and engineers to ensure safe AI deployment. The role emphasizes leadership in quantitative analysis and metric operationalization within a safety-focused team.

This role focuses on developing and implementing AI-first methods for measuring and monitoring complex harms on OpenAI's platforms. The Data Scientist will own measurement and metrics for severe usage harms, build productionised safety metrics, optimize LLM prompts for measurement, and leverage agentic products for automation. The role is crucial for ensuring the integrity and security of OpenAI's scaling technology.

Product-focused Data Scientist to shape AI-powered enterprise products like ChatGPT Enterprise and agentic automation systems. Focus on analyzing user interaction, informing product strategy, and building measurement frameworks for AI agents and automation workflows.

Data Scientist role focused on evaluating, improving, and building mitigation systems to prevent extreme harms from AI. This involves deep error analysis, root cause investigation, building monitoring frameworks, and identifying trends in blocking effectiveness to influence product and policy changes. The role requires strong analytical skills, SQL/Python proficiency, and experience in high-stakes domains like security or trust & safety.

This role focuses on applying agent-based systems to infrastructure delivery and operations within OpenAI's Stargate Infrastructure team. The goal is to use AI-driven approaches for deployment orchestration, system bring-up, issue triage, debugging, and capacity management, rather than building general-purpose agent platforms. It's a player-coach role involving direct system design and implementation while leading a small team.

OpenAI's Forward Deployed Engineer role focuses on partnering with strategic customers to deploy frontier AI models into production systems. This role involves end-to-end ownership of discovery, technical scoping, system design, build, and rollout, with a strong emphasis on driving customer adoption and using evaluation feedback to influence product and model roadmaps. The position requires deep technical expertise in building full-stack systems, understanding LLM behavior, and contributing code, while also acting as a liaison between customer teams and OpenAI's internal Research and Product groups. Fluency in both Japanese and English is a mandatory requirement.

Software Engineer focused on building and maintaining anti-abuse and content moderation infrastructure to ensure the safety, robustness, and reliability of AI models and their deployment. The role involves utilizing AI techniques to monitor and improve model alignment, diagnosing and remediating incidents, and developing tooling to address system failures. Experience with production services, debugging live issues, and understanding AI capabilities vs. risks is desired.

Product Engineer to build and own autonomous, customer-facing agentic systems that directly drive revenue and pipeline, interfacing with enterprise customers and revenue-critical workflows. The role involves full-stack development, applying OpenAI models in novel ways, and iterating based on live usage data.

Software Engineer, Research - Human Data role at OpenAI. Focuses on building and maintaining full-stack systems for feedback collection, data labeling, and evaluation pipelines to train and improve AI models. Partners with researchers to translate alignment research into scalable production infrastructure, including inference and model training stacks. Designs user-facing tools and backend services for high-quality data workflows, driving infrastructure improvements for OpenAI's frontier models.

Software Engineer focused on post-training research, building tooling and evaluation systems for researchers to prepare models for deployment in products like ChatGPT and the API. The role involves rapid prototyping, refactoring codebases, and designing experiment systems.

Security Engineer focused on securing agentic AI systems by designing and implementing security controls, policies, and tooling. The role involves threat modeling, collaborating with infrastructure and safety teams, and influencing security strategy for AI agents.

This role focuses on enabling systems integrators and their enterprise customers to deploy and scale Generative AI applications using OpenAI's models. The Partner AI Deployment Engineer acts as a technical lead and trusted advisor, helping partners identify use cases, build prototypes, provide strategic guidance, and ensure successful production deployments. The role involves close collaboration with internal teams (Sales, Solutions Engineering, Applied Research, Product) and external stakeholders (SI partners, customer executives) to drive tangible business value through AI adoption.

Engineering Manager to found and lead the ChatGPT Infrastructure team in London. This role involves building and scaling core runtime primitives and infrastructure for new ChatGPT experiences, requiring high ownership, technical leadership, and startup-style problem solving. The manager will establish engineering culture, hire and develop the team, and own system reliability.

This role focuses on leading complex deployments of OpenAI's frontier AI models for government and public sector customers. The Forward Deployed Engineer (FDE) will embed with clients to understand their problems, structure and build full-stack solutions, and ensure successful, compliant, and reliable deployments of AI tools like ChatGPT Enterprise and ChatGPT Gov. The role involves technical thought partnership, driving adoption, maximizing mission impact, and contributing to product roadmap through field feedback. It requires strong engineering skills, experience with LLM deployments, and the ability to manage customer relationships and technical delivery in high-stakes environments.

Manage a team of AI Deployment Engineers focused on the technical success of strategic technology and software customers in the Digital Native segment, ensuring seamless platform integration and driving Generative AI use cases to production.

Backend Software Engineer to design and build an evals infrastructure for measuring the quality of OpenAI's support automation. The role involves building robust systems and backend services, integrating data, and collaborating with data science and research partners. Experience with AI agents, LLM evaluation methods, and distributed systems is required.

AI Deployment Engineer role focused on guiding strategic startup customers in building and scaling novel applications on OpenAI's API. The role involves technical thought partnership, prototyping, providing business impact guidance, and synthesizing feedback for internal teams. It requires strong software engineering and AI/LLM best practices knowledge, with an emphasis on end-to-end problem ownership and collaboration within the startup ecosystem.

Backend Software Engineer to build core systems for search, matching, and recommendation for an AI-powered job platform. This role involves productionizing ML models, running experiments on ranking and recommendation strategies, and building scalable systems that support millions of users. Experience with vector databases, search indices, and ML concepts is required.

Solutions Engineer role focused on helping startup customers build and scale Generative AI applications using OpenAI's API. This involves technical guidance, product feedback synthesis, and creating reusable resources for the startup ecosystem.

Manager for Forward Deployed Engineering team at OpenAI, responsible for leading engineers in delivering production systems with frontier AI models to customers. The role involves owning end-to-end delivery outcomes, informing product and research roadmaps, and ensuring safe deployment at scale. Requires strong leadership, technical project management, and experience with customer-facing engineering.

This role focuses on leading end-to-end deployments of frontier AI models for strategic customers, involving discovery, technical scoping, system design, build, and production rollout. The engineer will build full-stack systems, embed with customer teams, and contribute code when necessary, with success measured by production adoption, workflow impact, and feedback that influences product and model roadmaps. The role requires experience with LLMs or generative models and delivering complex systems in ambiguous environments.

Software Engineer role focused on building AI-powered knowledge and automation systems using OpenAI's latest technologies. The role involves end-to-end development, collaboration with various teams, and iterating on applying models to internal use cases, with a focus on customer-facing systems like knowledge systems, automation systems, and automated agent systems.

Software Engineer focused on building the ecosystem, enterprise capabilities, and platform primitives for Codex, an AI software engineer. This role involves turning Codex into a production-grade teammate for organizations, enabling its deployment, operation, and trust in demanding real-world environments. Responsibilities include developing plugins, skills, discovery surfaces, RBAC, admin/audit features, usage controls, and analytics, as well as designing secure, observable full-stack systems integrated with enterprise identity and governance solutions. The role requires leading customer deployments and iterating based on live usage signals.

This role focuses on leading end-to-end deployments of AI models within life sciences organizations, translating customer needs into production systems, defining launch criteria for regulated environments, and designing evaluations to measure model and system quality. The role involves working closely with customers and internal teams to improve both customer systems and the product/model roadmaps.

Software Engineer role focused on building the cloud-based runtime and orchestration layer for the Codex AI agent, enabling it to securely and reliably execute tasks, interact with codebases, and operate at scale for enterprise customers. This involves designing and implementing core platform capabilities, including container orchestration, sandboxed environments, identity and governance systems, and observability, to support agentic experiences.

Forward Deployed Engineer (FDE) for Life Sciences at OpenAI, focusing on end-to-end deployment of AI models in regulated environments. This role involves partnering with customers to translate workflow needs into production systems, defining launch criteria, and using evaluation results to improve models and product roadmaps. Requires strong software/ML/deployment engineering experience and customer-facing ownership in biotech/pharma.

AI Deployment Engineer focused on helping customers adopt OpenAI's coding tools (Codex) by guiding them in integrating Codex into their projects and workflows, designing and validating advanced AI workflows, and building demos and integrations. This role involves technical architecture, product strategy, and customer-facing leadership, working closely with various internal teams and customers to accelerate the deployment of intelligent coding systems.

Software Engineer on the Platform Systems team at OpenAI, responsible for designing and building distributed systems for failure detection, tracing, and observability to support large-scale AI model training. The role focuses on improving the reliability, performance, and visibility of OpenAI's training infrastructure.

This role focuses on testing the safety and robustness of AI models through evaluations, red-teaming, and identifying failure modes. It involves leading programs to understand model behaviors, translating risks into research plans, and collaborating with research and engineering teams to integrate findings into model development and deployment cycles. The goal is to strengthen model reliability and public trust.

Lead a team responsible for enabling enterprise customers to successfully deploy and adopt OpenAI products, focusing on technical leadership, customer enablement, and people management. The role involves shaping scalable enablement programs for operationalizing AI technologies and partnering with Sales, Technical Success, and Product teams.

Engineering Manager to lead a team building software systems that detect and prevent harmful misuse of frontier AI models, focusing on model IP protection, distillation detection, and emerging risks from autonomous agents. The role involves setting technical roadmaps, building scalable production systems, and partnering with Research and Product to translate model capabilities into deployed mitigations. Requires strong software engineering fundamentals, experience in adversarial environments, and leadership skills.

This role focuses on helping enterprise customers adopt OpenAI's coding tools (Codex) by acting as a technical partner. The engineer will design, validate, and scale AI workflows, build demos and integrations, and provide technical enablement and content. The role involves close collaboration with sales, product, and applied engineering teams to gather customer feedback and influence product direction.

Software Engineer role focused on building and owning autonomous, customer-facing agentic systems that drive revenue and pipeline for OpenAI's marketing and sales organizations. The role involves full-stack development, API integration, orchestration, and applying OpenAI models to create AI-native products and workflows.

Manager for Forward Deployed Engineers (FDEs) in Life Sciences at OpenAI. Leads a team delivering production AI systems for drug discovery and development in regulated environments. Acts as a player-coach, responsible for delivery outcomes, team growth, technical direction, and ensuring high-quality, production-grade systems. Success is measured by team health, production adoption, workflow impact, eval-driven feedback, and deployment repeatability. Requires significant engineering and management experience, ideally in life sciences R&D or regulated scientific data.

OpenAI's Forward Deployed Engineering (FDE) team seeks a Technical Deployment Lead to manage the delivery of complex AI systems to customers. This role involves defining delivery plans, overseeing execution, embedding with customer teams, and ensuring adoption. Success is measured by customer impact, delivery reliability, and the ability to extract reusable patterns. The role requires strong technical project management, customer-facing experience, and a track record of shipping AI/LLM systems.

OpenAI's Training Runtime team is seeking a Process Management Engineer to build and maintain the distributed OS responsible for launching, coordinating, and supervising large-scale machine learning training workloads. This role involves working with Rust and Python to create high-performance, reliable, and observable systems that enable researchers to scale ideas from experiments to production training runs on massive clusters.

Product Manager for OpenAI's Memory & Personalization team, focusing on building systems for ChatGPT to learn from user interactions over time, remembering context, preferences, goals, and workflows to deliver tailored experiences. The role involves defining how ChatGPT adapts to individual users, balancing innovation with safeguards for user control, privacy, and transparency.

Forward Deployed Engineer to lead end-to-end deployments of OpenAI's AI models within semiconductor and chip design organizations, focusing on integrating AI into chip design, verification, and tooling workflows to reduce design cycles and improve quality. This role involves designing and shipping production AI systems, leading customer engagements, delivering AI-powered verification workflows, building systems over large codebases, and defining evaluation loops. Success is measured by production adoption, cycle-time reduction, and engineer productivity gains.

Product Manager focused on biosecurity risk for OpenAI's frontier models. The role involves driving initiatives to ensure safe and impactful deployments, developing safety-focused product roadmaps, and collaborating with cross-functional teams. Key responsibilities include creating scalable evaluation and improvement systems, integrating AI safety research, and defining metrics for safety performance.

OpenAI's Forward Deployed Engineering (FDE) team is seeking a Technical Deployment Lead (TDL) to own the delivery of complex AI systems to customers. This role involves defining delivery plans, managing day-to-day execution, embedding with customers to ensure adoption, and translating field insights back to Product and Research. Success is measured by customer impact, adoption, and delivery reliability. The role requires strong technical project management, customer-facing experience, and a track record of shipping AI/LLM systems.

Lead a team to build and own a performance modeling framework for AI infrastructure systems, analyzing tradeoffs across compute, memory, networking, and storage to guide architectural decisions and influence vendor roadmaps. Requires deep knowledge of AI/ML workloads (training/inference) and large-scale distributed systems.

Engineering Manager to lead a team building AI-powered automation systems for internal operations, focusing on autonomous reasoning and learning from humans. The role involves hands-on architecture, full-stack development, and rapid iteration with internal users and customers.

Investigate AI agentic and autonomous behavior risks, identify emerging patterns, and propose improvements to safeguards. Requires expertise in complex systems, multi-step behaviors, and ambiguous signals.

This role focuses on enabling the deployment of Generative AI applications for developers and enterprises by acting as a senior technical counterpart to AWS field leadership. The engineer will shape strategy, define engagement models, and build repeatable systems to scale adoption of OpenAI-powered solutions, guiding customers from ideation to production and enabling partners to independently drive deployments. The role involves designing AI architectures, building prototypes, establishing best practices for production-ready GenAI systems, and enabling the AWS ecosystem through scalable technical motions.

This role focuses on leading end-to-end deployments of frontier AI models in production for strategic customers, building full-stack systems, and driving adoption. It involves technical scoping, system design, build, and production rollout, with a strong emphasis on customer collaboration and measurable impact.

Seeking an experienced SoC Architect to define and develop next-generation custom AI silicon for edge deployments, focusing on efficient, high-performance SoCs for ML inference. The role involves cross-functional collaboration with internal teams and external partners to translate product requirements into scalable silicon solutions, driving execution from concept through delivery.

AI Deployment Engineer focused on helping customers adopt OpenAI's coding tools (Codex) by designing, implementing, and scaling AI-enhanced development workflows. This role involves acting as a technical partner, building demos and integrations, leading workshops, and gathering customer feedback to influence product direction.

AI Deployment Engineer for OpenAI's Codex, focusing on customer adoption of coding tools, designing and implementing AI-enhanced development workflows, building demos and integrations, and providing technical enablement and content.

AI Deployment Engineer focused on helping customers adopt OpenAI's coding tools (Codex) by designing, validating, and scaling advanced AI workflows. This role involves acting as a technical subject matter expert, building demos and integrations, leading workshops, and gathering customer feedback to influence product direction. It blends technical architecture, product strategy, and customer-facing leadership.

This role focuses on deploying complex AI systems, specifically for the Life Sciences vertical (pharmaceuticals, CROs), to customers. The Technical Deployment Lead will own the end-to-end delivery process, from defining technical plans and managing execution with internal teams (FDEs, Researchers) and customer teams, to ensuring adoption and measuring impact. The role requires translating business outcomes into technical plans, managing dependencies, and driving prototypes through MVP and scale, with a strong emphasis on customer value and adoption.

OpenAI is seeking a founding Technical Deployment Lead in Singapore to define and own the delivery of complex AI systems to customers. This role involves translating business outcomes into technical plans, managing day-to-day execution across engineering and customer teams, and ensuring successful adoption and measurable value delivery. The TDL will partner with Product and Research to guide the roadmap based on field insights and codify reusable patterns and evaluations.

Research Scientist focused on building scientific and evaluation infrastructure to understand how AI systems affect learning, cognition, and capability development over time. The role involves designing rigorous studies, developing scalable evaluation methods, and measuring cognitive outcomes beyond engagement. It sits at the intersection of learning science, cognitive science, experimental design, LLM evaluation, and applied product research, with an initial focus on young users and education settings. This is an applied, empirical role focused on building evidence systems that are scientifically credible, operationally useful, and influential in model and product development.

AI Deployment Engineer focused on working with strategic startup customers to optimize their use of OpenAI's technology, identify failure modes, and translate learnings into product improvements and better model behavior. The role involves prototyping prompts/agents, designing evaluations, and building repeatable tools to improve AI systems.

This role focuses on helping enterprise customers adopt OpenAI's coding tools (Codex) by acting as a technical partner. The engineer will design, validate, and scale AI workflows, build demos and integrations, and provide technical enablement. The role involves deep customer engagement, influencing product direction, and contributing to technical content.

AI Deployment Engineer focused on helping customers adopt OpenAI's coding tools (Codex) by acting as a technical partner, guiding integration, designing workflows, and building demos and automations. The role involves customer-facing leadership, technical architecture, and product strategy, with a focus on accelerating software development lifecycle through AI.

AI Deployment Engineer focused on working with strategic startup customers to optimize their AI systems, identify failure modes, and translate learnings into reproducible evaluations and product improvements for OpenAI. This role involves prototyping prompts/agents, designing evaluations, and acting as a technical partner.

Data Scientist on the Platform team at OpenAI, focusing on API and B2B solutions. The role involves defining metrics, measuring impact, and partnering with product and engineering to improve model quality, reliability, latency, and cost, ultimately shaping the adoption of agentic AI.

Director of Data Engineering and Agentic AI Automation for Finance at OpenAI. This role involves building scalable data infrastructure for financial operations and defining the roadmap for agentic AI automation to enable intelligent workflows and process automation. The role requires leading teams of data engineers, analytics engineers, and AI engineers, and ensuring data systems are AI-ready for predictive analytics and autonomous agent workflows.

Data Scientist focused on measuring and responding to adversarial threats and misuse on OpenAI's platforms, developing AI-first methods for prevalence estimation and productionised safety metrics, and optimizing LLM prompts for measurement. This role involves owning measurement and metrics for severe harm verticals, informing improvements to detection and enforcement, and leveraging agentic products for automation.

Data Scientist for ChatGPT for Work, focusing on shaping product strategy through data, defining core KPIs, building funnels, designing experiments, and translating insights into product direction for an AI-native workspace. Requires strong product sense, experimentation skills, and experience with B2B products and AI tools.

Data Scientist role focused on building and scaling anti-fraud and abuse detection systems for OpenAI's platform, utilizing LLMs and large datasets to combat evolving threats.

Software Engineer role focused on building the observability product for OpenAI, including scalable infrastructure for logs and metrics, and AI-native tools like agents for issue detection and debugging. The role involves owning core observability infrastructure and contributing to UI experiences, with a focus on making production systems reliable, performant, and observable. It's an engineering role within an AI company, building AI-powered internal tools.

Software Engineer focused on building systems to detect and prevent abuse, financial fraud, botting, and scripting on AI platforms. Collaborates with cross-functional teams to mitigate adversarial attacks and responds to incidents. Requires experience with production backend services and data pipelines, and a strong understanding of AI safety in production.

AI Deployment Engineer focused on partnering with media organizations to implement Generative AI solutions, driving them from prototype to production, and ensuring business value through technical guidance and architectural design using OpenAI API.

This role focuses on investigating sophisticated threat actors targeting OpenAI's models and infrastructure, building tooling and AI-assisted workflows to enhance threat detection, disruption, and safety improvements. The primary focus is on understanding adversary behavior and developing scalable solutions to combat misuse of AI models.

AI Deployment Engineer role focused on helping strategic startup customers build and scale novel applications on OpenAI's API, acting as a technical thought partner and providing guidance to maximize business impact. The role involves prototyping, synthesizing feedback, and contributing to open-source resources.

This role focuses on designing and executing data collection campaigns to support AI research and model development, particularly for LLMs. The TPM will collaborate with researchers and engineers to define data needs, build and optimize data platforms, and ensure data quality for training and evaluation purposes.

Senior Staff Software Engineer role focused on deploying OpenAI's AI technology to public sector customers, involving end-to-end feature development, infrastructure optimization, and cross-functional collaboration with product, security, and compliance teams. The role requires experience with web technologies, backend languages, and infrastructure primitives, with an interest in AI/ML.

Software Engineer focused on building and scaling backend infrastructure for AI-powered knowledge and automation systems. The role involves designing, building, and maintaining backend services, APIs, and data pipelines that integrate OpenAI models into high-leverage workflows, supporting internal and external customers. The team iterates fast and engineers for reliable long-term impact, focusing on building simple primitives to apply knowledge to many domains.

AI Deployment Engineer role focused on helping strategic startup customers build and scale novel applications on OpenAI's API, acting as a technical thought partner and feedback conduit to internal teams.

Backend Software Engineer for the GTM Innovation team, focused on building and shipping AI-powered applications and tools to enhance OpenAI's go-to-market efforts. This role involves working across the full product lifecycle, partnering with go-to-market teams, and applying OpenAI's models to solve real-world problems, ultimately shaping customer experience and defining new enterprise software categories.

OpenAI is seeking an experienced Performance Engineer to optimize the performance, reliability, and efficiency of their AI systems, including ChatGPT and the OpenAI API. The role involves deep technical expertise in analyzing and optimizing infrastructure and application layers, developing observability tooling, influencing architecture, and leading investigations into performance issues. This is an individual contributor role focused on high-scale distributed systems.

This role focuses on deploying Generative AI applications for public sector customers, acting as a technical advisor to help them identify, build, and scale AI use cases using OpenAI's API and products. The engineer will partner with customer technical teams and implementation partners to move from prototype to production, ensuring tangible value and contributing to the growth of the AI Deployment Engineering function.

Software Engineer role focused on building scaled foundational systems for detecting, tracking, and enforcing harm on OpenAI's platforms, leveraging advanced AI technologies to automate and augment these processes. The role involves collaboration with various experts and staying ahead of adversarial threats.

Software Engineer focused on building the ecosystem, enterprise capabilities, and product experiences for Codex, an AI software engineer. This role involves working across the full stack to enable deployment, operation, and trust of Codex in demanding real-world environments, including integrating with enterprise identity and governance systems, and leading customer deployments.

Fullstack Engineer focused on developing and maintaining intelligence systems to detect and disrupt AI abuse, ensuring safe and responsible AI use. The role involves prototyping, building scalable systems, analyzing data, and acting as a technical bridge between data scientists and other technical teams.

AI Success Engineer role focused on post-sales customer engagement, driving adoption, technical integration, and value realization of OpenAI's AI platform for enterprise clients. This role requires deep technical knowledge of OpenAI products, APIs, and common integration patterns, along with experience in enterprise security and compliance. The engineer acts as a trusted advisor, mapping workflows, guiding deployments, and translating customer needs into actionable roadmaps, while also providing feedback to Product, Engineering, and Research teams.

The role focuses on building tooling and infrastructure for creating high-coverage, realistic virtual environments for robotics research and evaluation. This involves designing content pipelines, authoring procedural generators, and shipping tools for environment creation, quality control, and integration with simulation farms and ML evaluation pipelines. The role sits at the intersection of game-engine practice, asset engineering, and large-scale simulation infrastructure.

This role focuses on designing and building systems to identify and enforce abuse on OpenAI's products, leveraging data science, ML, and investigation. It involves developing monitoring for new and existing products, prototyping detection and enforcement systems, and investigating critical escalations. The role requires experience with SQL, Python, data engineering, ML principles, and scaling processes with language models.

This role focuses on detecting, investigating, and disrupting the misuse of OpenAI's AI platform. The investigator will develop and scale investigative processes, build technical solutions like data pipelines and utilities, and collaborate with various teams to improve detection and enforcement strategies. The role requires technical fluency in navigating complex datasets and automating manual processes, with a focus on agentic AI misuse and other relevant domains.

Full Stack Software Engineer for the GTM Innovation team, focusing on building and shipping applications that leverage OpenAI's models to improve go-to-market efforts. This role involves working across the full product lifecycle, from prototype to production, and collaborating closely with go-to-market teams to understand user needs and solve real-world problems.

Product Engineer on the GTM Innovation team at OpenAI, responsible for building and shipping high-impact applications and tools using OpenAI's API platform to accelerate go-to-market efforts. This role involves working across the full product lifecycle, embedding with go-to-market teams to identify user needs, and applying OpenAI's models in novel ways to solve real-world problems. The ideal candidate has experience building user-facing systems, LLM-powered workflows, and a strong sense of ownership.

Full-Stack Software Engineer for OpenAI's Incubation team, focused on exploring, prototyping, and building new AI-powered product ideas from 0 to 1. This role involves working across the full stack in a fast-paced, ambiguous environment, turning early concepts into validated products that can scale.

This role focuses on designing and building systems to proactively identify and enforce abuse on OpenAI's products, including developing abuse monitoring for new and existing products, and prototyping systems for detection, review, and enforcement. It involves investigating critical escalations and working cross-functionally with product, policy, and engineering teams. The role requires technical analysis, data engineering, and machine learning principles, with an emphasis on scaling and automating processes, particularly with language models.

AI Deployment Manager at OpenAI, focused on post-sales technical enablement and adoption of AI products like ChatGPT Enterprise, Codex, and Agents. This role involves designing and delivering training, workshops, and adoption programs to help enterprise customers effectively use and integrate OpenAI's AI capabilities, translating technical features into measurable business value.

This role focuses on enabling strategic customers and partners to effectively deploy and integrate OpenAI's ChatGPT and API applications. The AI Deployment Engineer will act as a technical resource, driving solution design, co-developing innovative experiences, and guiding partners on best practices for leveraging OpenAI's platform. The role involves collaborating with internal teams (Partnerships, Product, Engineering, GTM) and external stakeholders to ensure successful and valuable adoption of OpenAI's products.

This role focuses on post-sales technical enablement and adoption of OpenAI's AI products (ChatGPT Enterprise, Codex, Agents, API) for enterprise customers. The AI Deployment Manager designs and delivers training, workshops, and adoption programs to drive customer activation, usage, and business value, acting as a bridge between customers and product/engineering teams.

Software Engineer focused on improving the developer experience and productivity within OpenAI's core training and inference frameworks. This role involves optimizing iteration speed, CI, and testing strategies to support researchers working on frontier experiments.

Forward Deployed Engineer (FDE) for financial services at OpenAI, responsible for leading end-to-end deployments of AI models within customer organizations. This role involves technical scoping, system design, build, and production rollout, with a focus on driving customer adoption and measuring workflow impact. The FDE will partner closely with customer teams, product, research, and GTM teams, and contribute to product and model roadmaps through field feedback.

Manager for AI Success Engineers focused on driving adoption and value realization of OpenAI's AI products (specifically ChatGPT Enterprise) for enterprise customers. This role involves leading a technical team, developing strategy, ensuring customer onboarding and activation, and representing customer needs to product teams.

Seeking a Simulation Realism Engineer to improve the accuracy of simulation environments for robotics research and product development. This role involves defining realism metrics, tuning simulation parameters, integrating third-party engines, and developing tooling and pipelines for large-scale simulation operations. The goal is to close the sim-to-real gap for AI-powered robots.

Product Manager for OpenAI's Integrity team, focusing on scaling product efforts and technical strategy to combat scaled abuse and novel misuse of AI services like ChatGPT, API, and Sora. Requires close collaboration with product, safety, policy, operations, and engineering teams to build tooling and infrastructure for detection and prevention of policy violations.

AI Deployment Engineer role focused on helping enterprise customers integrate and deploy Generative AI solutions using OpenAI's API, acting as a technical advisor and solutions leader to drive business value and production readiness.

AI Deployment Engineer role focused on helping enterprise customers integrate and deploy Generative AI applications using OpenAI's API and models. The role involves strategic guidance, technical leadership, building prototypes, and ensuring successful production deployment.

AI Success Engineer role focused on partnering with enterprise customers to drive adoption and business value from OpenAI's AI platform. This post-sales role involves technical leadership, customer advisory, and influencing product development by translating customer needs and feedback.

AI Success Engineer role focused on post-sales customer engagement, driving adoption, technical integration, and value realization of OpenAI's AI platform for enterprise clients. This role acts as a trusted advisor, bridging technical capabilities with business goals and influencing product development through customer feedback.

AI Success Engineer role at OpenAI, focused on post-sales customer engagement to drive adoption and business value of OpenAI's AI platform. Responsibilities include technical relationship management, identifying use cases, guiding deployments, and acting as a trusted advisor for enterprise clients. Requires deep technical knowledge of OpenAI products, APIs, and integration patterns, along with experience in enterprise security and customer-facing technical roles.

AI Success Engineer role focused on post-sales customer engagement, driving adoption, technical integration, and value realization for enterprise clients using OpenAI's AI platform. This role requires deep technical knowledge of OpenAI products, APIs, and common integration patterns, as well as experience with enterprise security and compliance frameworks. The engineer will act as a trusted advisor, identify use cases, lead deployments, and translate customer needs into actionable roadmaps, while also providing feedback to Product, Engineering, and Research teams.

Manager for Integrity Data Science team at OpenAI, focusing on responsible AI deployment. The role involves leading a team to build measurement systems, experimentation practices, and detection/mitigation strategies against misuse, fraud, and adversarial behaviors. Key responsibilities include driving strategy across multiple integrity domains, building analytical rigor, partnering with Product & Engineering, and evolving team structure. The role emphasizes an AI-leveraged operating mode and requires strong leadership, technical grounding in DS techniques, and experience in adversarial problem spaces.

AI Success Engineer role focused on post-sales customer engagement, driving adoption, technical integration, and value realization of OpenAI's AI platform for government customers. This role requires deep technical understanding of OpenAI products, customer advisory skills, and program management to guide customers from initial deployment to scaled enterprise adoption.

Full-stack engineer to build and ship AI-powered learning experiences within ChatGPT, focusing on multimodal capabilities and user-facing product features. The role involves end-to-end ownership from concept to production, collaborating with AI research and platform teams to translate AI advancements into consumer products.

This role focuses on developing and implementing policies for AI models concerning chemical and biological risks. It involves creating structured policy frameworks and taxonomies to guide safe model behavior, translating biosecurity expertise into actionable model policies, and identifying emerging risk vectors. The role sits at the intersection of biosecurity expertise, AI safety research, and policy design, aiming to reduce misuse risks while enabling beneficial research.

Platform Engineer within Forward Deployed Engineering (FDE) at OpenAI. This role focuses on building new platform capabilities from scratch, grounded in real customer deployments. The engineer will partner with customer-tagged FDEs to provide hands-on leverage in architecting, product shaping, refactoring, hardening, and creating reusable abstractions. The goal is to translate cross-customer patterns into platform bets and raise the engineering bar through tooling and mentorship, ultimately contributing to shipped software, repeatable patterns, and durable products.

This role focuses on identifying and mitigating emerging risks and potential harms associated with frontier AI technologies. The analyst will use strategic foresight, quantitative and qualitative methodologies to scan signals, detect abuse patterns, and translate findings into actionable intelligence and risk mitigation proposals. Key responsibilities include mapping risks, building early warning systems, and contributing to product safety readiness.

Manager for AI Success Engineers focused on driving adoption and value realization of OpenAI's AI products (ChatGPT Enterprise, Codex, custom GPTs) for enterprise customers, involving post-sale technical success, onboarding, and strategic partnerships.

Platform Engineer within Forward Deployed Engineering (FDE) to build new platform capabilities from scratch, grounded in real customer deployments. This role involves partnering with customer-tagged FDEs to provide hands-on leverage in architecting, product shaping, refactoring, and building, turning repeated customer signals into platform bets and raising the engineering bar through tooling and mentorship.

This role is a founding Technical Deployment Lead (TDL) for the FDE Platform team at OpenAI. The primary focus is on making early design partner deployments successful, from scoping to production adoption and demonstrated value. The role involves driving alignment across OpenAI and customer stakeholders, managing delivery plans, ensuring enterprise constraints (security, auditability, infra) are handled, and converting learnings into actionable improvements. Success is measured by delivered outcomes, adoption in critical workflows, and platform reliability.

Manager for AI Deployment Engineering focused on the Health & Life Sciences sector, responsible for leading a team to implement and scale generative AI systems for customers in regulated environments. Requires strong technical foundation, people leadership, and understanding of healthcare compliance.

This role focuses on co-designing hardware with vendors to optimize it for AI workloads, specifically for training and inference of large language models. It involves understanding ML techniques, algorithms, and numerical approximations to influence future hardware architectures and improve performance. The engineer will also build system performance models and evaluate potential accelerators.

This role focuses on leading technical delivery with OpenAI partners across EMEA, helping scale customer deployments built on the OpenAI platform. The engineer will support the design, deployment, and scaling of production-grade AI solutions through partners, ensuring quality, safety, and reliability. Responsibilities include acting as a primary technical delivery partner, translating designs into deployable architectures, providing integration support, and contributing to reusable deployment patterns.

This role is a post-sales AI Success Engineer responsible for driving technical success, adoption, and value realization for OpenAI's enterprise customers. The role involves acting as a trusted advisor, diagnosing issues using logs and telemetry, leading interventions, translating customer goals into adoption plans, conducting technical enablement, identifying repeatable use cases, and coordinating cross-functionally. The goal is to accelerate adoption, increase activation depth, guide strategic use cases to production, and help customers demonstrate tangible business impact.

Research Engineer focused on 3D and multi-view geometry for robotics, developing systems for perception, localization, and reconstruction from multi-camera sensor data. Integrates classical geometry with modern ML for real-time and large-scale pipelines.

Manager for AI Deployment Engineering focused on the Health & Life Sciences sector, responsible for leading a team to implement and scale production deployments of generative AI systems for customers in regulated environments. The role involves strategic planning, team management, establishing operational standards, and ensuring secure, compliant AI adoption.

AI Success Engineer role focused on post-sales customer engagement, driving adoption, technical integration, and value realization of OpenAI's AI platform for enterprise clients. This role acts as a trusted advisor, bridging technical and business needs, and influencing product development through customer feedback.

This role focuses on enabling organizations to adopt and operationalize OpenAI products, including ChatGPT Enterprise, Codex, Agents, and the API. The AI Deployment Manager will design and deliver technical enablement experiences, lead customer training, and partner with internal teams to drive product adoption and measurable business value. The role requires strong technical fluency, instructional design, and customer advisory skills, with an emphasis on translating technical features into tangible business outcomes.

Software Engineer to enable production workloads and end-to-end testing on new platforms for AI infrastructure. This role involves creating test harnesses, porting inference and training workloads, analyzing performance, and characterizing system behavior.

Lead a team responsible for enabling enterprise customers to successfully deploy and adopt OpenAI products, focusing on technical leadership, customer enablement, and people management. The role involves shaping scalable enablement programs for operationalizing AI technologies, partnering with Sales, Technical Success, and Product teams, and driving customer activation and business value.

This role focuses on building an AI-powered jobs platform, acting as a career agent to match workers with opportunities. The engineer will own product surfaces end-to-end, design core systems for matching and verification, and integrate new model and agent capabilities into production features. The role emphasizes building high-trust, scalable systems and iterating quickly based on user impact, working across the full stack.

Software Engineer focused on building internal tools and systems to detect and prevent abuse, promote user safety, and reduce risk across OpenAI's AI platforms. The role involves designing APIs, constructing investigation tools with access controls and auditability, and collaborating with cross-functional teams to mitigate adversarial attacks.

Software Engineer focused on kernel performance and AI tooling, working on AI-assisted workflows, developer tooling, observability, and optimizing production kernels for AI workloads. The role involves improving AI-assisted optimization systems and partnering across research and engineering teams.

Product Manager for Safety Measurement at OpenAI, responsible for defining the strategy and roadmap for platforms that measure harm and safeguard efficacy in production. This role involves partnering with research and engineering teams to integrate AI safety research into measurement products and represent quantitative safety progress to leadership.

AI Deployment Engineer focused on helping customers adopt OpenAI's coding tools (Codex) by acting as a technical partner. The role involves designing, validating, and scaling AI workflows, building demos and integrations, leading workshops, and gathering customer feedback to influence product direction. It requires deep technical expertise in AI coding tools and the software development lifecycle, with a strong emphasis on customer-facing post-sales engineering and solutions architecture.

AI Success Engineer role at OpenAI, partnering with enterprise customers to drive adoption and value realization of OpenAI's AI platform. Responsibilities include technical relationship management, enablement, use case identification, deployment planning, and cross-functional collaboration. Requires deep technical knowledge of AI products, APIs, and integration patterns, with strong project management and customer advisory skills.

Product Manager for AI Solutions in Enterprise Platforms, focusing on Finance and other core business functions. The role involves identifying, shaping, and scaling AI-enabled products and workflows, including copilots and agentic systems, by partnering with stakeholders, defining roadmaps, driving delivery, and measuring business value. Experience with enterprise applications, AI product delivery, and cross-functional leadership is required.

This role focuses on enabling the safe and effective deployment of Generative AI applications for developers and enterprises by serving as a technical advisor to AWS field leadership and partners. The engineer will drive joint customer success, shape strategy, define engagement models, and build repeatable systems to scale adoption of OpenAI-powered solutions. Responsibilities include leading technical strategy for complex engagements, guiding customers from ideation to production, designing end-to-end AI architectures, building prototypes, establishing best practices for scalable GenAI systems, and enabling AWS and partners through workshops and playbooks. The role requires strong technical leadership, systems thinking, and the ability to balance hands-on building with strategic influence.

This role focuses on empowering developers to integrate AI into their applications by creating demos, tools, and technical content showcasing OpenAI's models and APIs. It involves engaging with the developer community, representing OpenAI at events, and gathering feedback to improve products.

This role involves investigating sophisticated threat actors targeting OpenAI's models and systems, building tooling and AI-assisted workflows to scale analysis, and translating findings into security improvements. The focus is on understanding adversary behavior, identifying misuse, and developing proactive defenses.

Product Manager for OpenAI's Safety Systems team, focusing on cybersecurity risk for frontier AI models. The role involves driving initiatives to ensure responsible deployment, developing safety roadmaps, and collaborating with research, engineering, and policy teams. Requires experience in AI safety, trust & safety, or integrity, with a background in cybersecurity and strong product management skills.

Product Manager for Integrity team focusing on sensitive AI deployments, including government, regulated enterprise, privacy-constrained environments, and agentic workflows. The role involves defining product strategy, measuring risk, building agentic investigation workflows, and creating launch playbooks for high-risk domains.

This role focuses on designing and building AI-native workflows, automations, and internal tools to accelerate OpenAI's Go-To-Market (GTM) organization. The engineer will work at the intersection of Revenue Operations, AI product development, systems design, and workflow engineering, using OpenAI's products and APIs to solve operational problems in areas like forecasting, pipeline management, and customer execution. The goal is to create practical AI systems that improve field productivity and operational scale.

OpenAI is seeking an experienced Design Verification Engineer to join their Forward Deployed Engineering team, focusing on deploying AI systems in semiconductor design. The role involves serving as a technical SME for verification workflows, shaping AI-assisted processes, curating evaluations, and building prototypes. Over time, the role will expand to broader FDE responsibilities including customer partnership, solution building, and deployment ownership.

Lead engineering for generative AI and reinforcement learning in autonomous vehicle technology, focusing on agentic software systems, end-to-end integration, and data-driven innovation using real-world and synthetic data.

Lead engineering for AI-driven autonomous vehicle technology, focusing on deep learning and reinforcement learning to develop advanced agentic software systems and integrate them into production-ready systems. This role involves research, experimentation, and utilizing real-world and synthetic data for model enhancement, with a strong emphasis on shipping end-to-end products.

Lead engineering efforts for generative AI in autonomous vehicle technology, focusing on deep learning, reinforcement learning, and agent-based systems. The role involves designing and implementing novel algorithms, integrating prototypes into production, and utilizing real-world and synthetic data for training. Requires experience shipping products end-to-end and knowledge of LLMs and RL.

The AI Sorcerer role at Anduril focuses on designing, implementing, and evolving agentic systems that interact with classical software. This involves contributions to test and evaluation infrastructure, agent tool calling, prompt engineering, and improving agent performance and interaction patterns within the Lattice OS for defense applications.

Head of Frontier AI to build and lead a machine learning team focused on instantiating safe and secure agentic and perception capabilities for defense programs. This role involves driving strategy, managing engineers and researchers, providing technical leadership, leveraging large defense robotics datasets, coordinating with testing teams, and partnering with research labs to revolutionize autonomy in embedded hardware. Requires management experience, experience deploying AI in classified environments, and expertise in deep learning and generative AI (Agents, VLAs).

Anduril Industries is seeking a Generative AI Integration Engineer to design, implement, and evolve agent interactions with classical software systems. This role involves contributing to test and eval infrastructure, deployment software, agent tool calling, prompt engineering, and other agent techniques to achieve high performance with frontier and edge models. The engineer will enhance agentic interaction patterns and expand agent interaction capabilities within the Lattice system.

Research Scientist at Anduril, a defense technology company, focusing on developing state-of-the-art algorithms and software for military applications. The role involves creating mathematically principled solutions, prototyping algorithms, implementing high-performance software, and using simulation environments to quantify technology benefits. Requires an MS or PhD in a related field and a record of academic excellence, with a focus on applied AI/ML in defense.

Senior Machine Learning Engineer to lead the design, development, integration, and support of ML models for perception and data pipelines for autonomous systems in a defense technology company. The role involves managing the ML lifecycle, including data management, training, validation, evaluation, deployment, and regression testing, with a focus on production-grade software systems and MLOps in a classified environment.

Senior Machine Learning Engineer focused on perception systems for defense technology. This role involves designing, training, and deploying computer vision and perception models for edge-compatible, mission-critical environments, fusing multi-sensor data, and integrating ML algorithms into production systems. The position also requires developing evaluation frameworks and partnering with cross-functional teams to deliver operational capabilities.

Senior Machine Learning Engineer at Anduril, a defense technology company, focusing on developing and deploying multi-sensor object detection models and learning algorithms for autonomous systems on edge compute devices. The role involves owning the end-to-end ML stack, including data infrastructure, training, and optimizing on-device inference for real-time applications in a defense context.

Senior ML/MLOps Engineer to lead the design, deployment, and sustainment of an AI-enabled backbone for a digital shipbuilding environment. Focuses on operationalizing advanced models and architecting the industrial AI stack, integrating components like feature stores, vector databases, orchestration, and model-serving frameworks. Will translate factory scenarios into applied AI capabilities with human-in-the-loop controls and integrations with production systems.

Senior Research Scientist at Anduril, a defense technology company, focusing on developing state-of-the-art algorithms and software for AI-powered systems, including autonomy, computer vision, and sensor fusion. The role involves creating mathematically principled solutions, prototyping algorithms, implementing high-performance software, and engaging with customers to ensure successful outcomes for mission-critical needs. Requires an MS or PhD in a related field and a record of academic excellence.

Research Scientist at Anduril, a defense technology company, focusing on developing state-of-the-art algorithms and software for military applications. The role involves prototyping, implementing high-performance software, and engaging with customers to ensure successful outcomes for mission-critical needs. Requires an MS or PhD in a related field and a strong academic record.

Senior Research Scientist at Anduril, a defense technology company, focusing on developing state-of-the-art algorithms and software for military applications. The role involves prototyping, implementing high-performance software, and quantifying technological benefits using advanced tools. Requires an MS or PhD in a related field, experience with Rust, C++, and Python, and strong communication skills. The role is focused on research and development of AI/ML solutions for defense systems.

Senior Research Scientist at Anduril, a defense technology company, focusing on developing state-of-the-art algorithms and software for military applications. The role involves contributing to team direction, creating mathematically principled solutions, prototyping algorithms, implementing high-performance software, and engaging with customers. Requires an MS or PhD in a related field and a record of academic excellence. The company utilizes an AI-powered operating system called Lattice OS for command and control.

Research Scientist at Anduril, a defense technology company, focusing on developing state-of-the-art algorithms and software for military applications. The role involves prototyping, implementing high-performance software, and engaging with customers to ensure successful outcomes for mission-critical needs. Requires an MS or PhD in a related field and a strong academic record.

Anduril Industries is a defense technology company seeking an Applied Machine Learning Engineer to build edge-compatible, generative AI systems into their Lattice software platform. The role involves distilling and fine-tuning transformer architectures for edge deployment, proposing and prototyping LLM-based Agentic systems, developing mission-relevant benchmarks, and collaborating with business lines. Requires BS in CS/ML/EE, 5+ years in ML algorithm development and benchmarking, production ML experience, strong Python and PyTorch skills, and U.S. Person status. Preferred qualifications include experience with fine-tuning transformers and deploying deep learning models to edge/air-gapped environments.

Computer Vision Engineer for autonomous aerial platforms, focusing on 3D perception, SLAM, and integration with path planning and autonomy systems in a defense technology company.

Anduril's Space team is seeking a Computer Vision Engineer to develop and integrate perception subsystems for spacecraft missions. This role involves algorithm design, simulation, and implementation of classical and ML-based computer vision techniques for tasks like object detection, tracking, segmentation, and visual odometry, contributing to autonomous spacecraft operations and Space Domain Awareness.

Anduril's Space team is seeking a Computer Vision Engineer to develop and implement AI-powered perception subsystems for spacecraft. This role involves algorithm design, ML integration, software/hardware development, and validation for various space missions, focusing on autonomous operations and enhancing Space Domain Awareness. The position requires expertise in computer vision, ML, C++ development, and a strong understanding of space systems and defense applications.

Software engineer specializing in machine vision for guidance systems on air vehicles, involving image processing, sensor fusion, and real-time algorithm development using Python and C++.

Senior Computer Vision Engineer role focused on developing advanced perception systems for autonomous aerial platforms, integrating computer vision algorithms with robotics principles for real-time decision-making, SLAM, and path planning. The role involves developing robust algorithms, integrating perception outputs with path planning, designing experiments, and collaborating with cross-functional teams.

Senior Computer Vision Engineer for Anduril's Space team, focusing on developing and integrating AI-powered computer vision subsystems for spacecraft operations, including navigation, perception, and autonomous maneuvering. The role involves algorithm design, ML integration, and ensuring the successful implementation and validation of CV systems for various space missions, requiring a strong background in C++, ML algorithms, and computer vision techniques.

Senior Computer Vision Engineer for Anduril's Space team, focusing on developing and integrating AI and computer vision systems for spacecraft operations, including perception subsystems, navigation algorithms, and autonomous capabilities. The role involves algorithm design, simulation, implementation, and validation for various space missions, with a strong emphasis on ML methods and classical computer vision techniques.

Senior Research Scientist at Anduril, a defense technology company, focusing on developing state-of-the-art algorithms and software for military applications. The role involves prototyping, implementing high-performance software, and engaging with customers to ensure successful outcomes for mission-critical needs. Requires an MS or PhD in a related quantitative field and a strong academic record.

Anduril is seeking a Senior Software Engineer to build the infrastructure for agentic software development, focusing on multi-agent orchestration, real-time knowledge bases for AI agents, and a skills/plugin platform. The role also involves improving CI/CD and operating the company's LLM adoption platform.

Senior Software Engineer on the Discovery team at Anduril, focusing on incubating and maturing AI-native offerings for defense applications. The role involves standing up infrastructure, simulation solutions, and integrations for agent development and training, collaborating with customers and other engineering teams, and deploying software in fielded environments. Requires experience in data processing, containerization, and Kubernetes, with a preference for ML training infrastructure and simulation expertise.

The Technical Program Manager, AI Platform role at Anduril focuses on driving the end-to-end execution of AI programs within the defense technology company. This involves partnering with various engineering and product teams to translate ambiguous problems into technical plans, establishing program operating rhythms, and implementing AI-enabled automation and agentic workflows to improve engineering and business operations. The role also supports the adoption of frontier AI tooling and AI-native development practices, aiming to make Anduril an autonomous enterprise.

Lead the development and integration of AI and autonomy technologies for air vehicles within a defense technology company. Focus on transforming military capabilities with advanced systems powered by an AI operating system.

Lead the development and integration of AI and autonomy technologies for air vehicles within a defense technology company. Focus on transforming military capabilities with advanced systems powered by an AI operating system.

Chief Engineer role at Anduril, a defense technology company, focusing on leading inter-disciplinary teams to develop and deliver integrated AI-powered systems for military applications. The role involves setting technical vision, defining system architecture, establishing best practices, and ensuring technical delivery and safety for products like Lattice OS, which uses AI for command and control. Requires significant experience in autonomous systems, robotics, and defense applications, with a strong emphasis on technical leadership and program execution.

Anduril Industries is hiring a C++ Mission Software Engineer for their Mission Autonomy team, focusing on developing aerial and multi-domain robotic systems. The role involves building the Lattice OS platform that enables robots to collaborate across missions, requiring expertise in autonomy software stacks including computer vision, motion planning, SLAM, controls, and estimation. The position requires strong C++/Rust experience and the ability to work with complex systems in a defense technology context.

This role focuses on the development, testing, and operational deployment of small drones and their associated systems, particularly those powered by an AI-driven operating system. The specialist will be involved in rapid prototyping, validation of algorithms, and ensuring systems meet warfighter needs in a defense technology context.

The Field Test Engineer, Maritime role at Anduril Industries focuses on testing and advancing subsea robotics, which are powered by an AI-driven operating system (Lattice OS). The role involves integrating AI, computer vision, and sensor fusion technologies into military systems, with a primary focus on delivering AI-enabled products to the defense sector.

The Field Test Engineer, Maritime role at Anduril focuses on testing and advancing subsea robotics and AI-powered systems for defense applications. This involves working with AI-powered operating systems, autonomy, computer vision, and sensor fusion in a dynamic, collaborative environment, with a primary focus on shipping AI-enabled products and secondary involvement in agentic systems.

The Flight Sciences Engineer will develop and validate guidance and control laws, perform hardware and software in-the-loop testing, and create cutting-edge navigation solutions for Anduril's autonomous drone fleet. This role is part of the Tactical Recon and Strike team, which builds aerial small drones and their operational systems, leveraging an AI-powered operating system for real-time command and control.

The Flight Sciences Engineer will develop and validate guidance and control laws, perform hardware and software in-the-loop testing, and create cutting-edge navigation solutions for Anduril's autonomous drone fleet. This role is part of the Tactical Recon and Strike team, focusing on small aerial drones and their operational systems, including navigating contested and GPS-denied environments.

Anduril Industries is seeking a Flight Test Operator to support and operate aircraft for software and system development, focusing on building, programming, and maintaining autonomous aircraft. The role involves acting as a safety pilot, operating ground control software, and supporting integrations with test engineers and system integrators. Experience with flight controllers, autopilot logic, and national airspace regulations is required.

Full Stack Software Engineer at Anduril Labs, focusing on developing innovative prototypes for defense technology, including autonomous systems and GenAI applications. Requires strong software development skills, experience with AI/ML concepts, and full-stack development across various environments.

Lead Robotics Software Engineer at Anduril, a defense technology company, focusing on developing and integrating autonomous systems, including drones and robotics. The role involves leading software development, mentoring engineers, optimizing performance, and collaborating across hardware and manufacturing teams. Key responsibilities include developing core robotics libraries, building simulators, and contributing to multi-agent coordination systems.

Lead Software Engineer for autonomous underwater vehicles, focusing on decision-making, autonomy, navigation, and mission execution software. This role involves system architecture, development processes, customer engagement, and core library development for robotics platforms.

Lead Software Engineer for autonomous underwater vehicles, focusing on decision-making, autonomy, navigation, and mission execution software. This role involves system architecture, development processes, customer engagement, and core library development for robotics platforms.

The Mission Software Engineer role at Anduril focuses on developing and deploying software solutions for defense systems, involving networking, autonomy, systems integration, and robotics. The role requires owning deployed software, writing code for product improvement and scaling, collaborating across teams, analyzing metrics, triaging issues, and partnering with end-users. A strong engineering background, experience with C++, Rust, or Python, and data processing skills are core requirements. Desired experience includes multi-agent autonomous systems, behavior trees, and flight systems.

Anduril Industries is hiring a Mission Software Engineer for their Air Vehicle Autonomy team. This role focuses on developing aerial and multi-domain robotic systems, specifically contributing to the autonomy software stack which includes computer vision, motion planning, SLAM, controls, and estimation. The position requires strong C++ or Rust experience and the ability to work with complex systems in a defense technology context.

Software Engineer role focused on developing aerial and multi-domain robotic systems, including autonomy software stacks with computer vision, motion planning, and multi-agent systems. The role involves taking products from concept to deployment in real-world environments for defense applications.

Software Engineer role focused on developing aerial and multi-domain robotic systems, including autonomy software stacks with computer vision, motion planning, and multi-agent systems. The role involves taking products from concept to deployment in real-world environments for defense applications.

Anduril Industries is a defense technology company building AI-powered operating systems and advanced autonomy, AI, computer vision, sensor fusion, and networking technology for military systems. This Mission Software Engineer role focuses on owning and deploying software solutions, improving products, scaling capabilities, and collaborating across teams to build and test complex functionality, with a strong emphasis on autonomy and multi-agent systems.

Anduril Industries is a defense technology company building AI-powered operating systems and advanced autonomy, AI, computer vision, sensor fusion, and networking technology for military systems. This Mission Software Engineer role focuses on owning and deploying software solutions, improving products, scaling capabilities, and collaborating across teams to build and test complex functionality, with a strong emphasis on autonomy and multi-agent systems.

Anduril Industries is seeking a Mission Software Systems Engineer to design, integrate, and manage complex, software-intensive mission autonomy systems based on their AI-powered Lattice OS for autonomous surface vehicles (ASVs). The role involves the full lifecycle from ConOps to maintenance, with a focus on integrating mission systems with vehicle and payload management, and supporting simulation and testing.

Lead the technical development and integration of vehicle mission systems for a defense technology company, focusing on AI-powered operating systems, autonomy, computer vision, and sensor fusion for military applications. This role involves driving architecture selection, leading cross-functional teams, and ensuring the delivery of operational mission systems from concept to deployment, with a strong emphasis on safety-critical software and integration with vehicle management systems.

Lead the technical development and integration of vehicle mission systems for a maritime product, from concept through delivery. This involves driving architecture selection, hardware/software integration, and leading teams to develop and test software for robotic mission systems, with a focus on autonomy and AI capabilities in a defense context.

Principal Mission Systems Lead at Anduril, a defense technology company. The role focuses on leading the technical development and integration of vehicle mission systems for Maneuver Dominance platforms. This involves driving architecture selection, hardware/software integration, service orchestration, and full lifecycle testing for robotic mission systems. The position requires experience in delivering military mission systems, distributed software platforms, and high assurance safety-critical software, with a deep understanding of autonomous weapons systems.

This role is for a Program Chief Engineer at Anduril Industries, a defense technology company. The focus is on leading autonomous systems for air defense, integrating AI, computer vision, and sensor fusion. The role involves stakeholder engagement, technical ownership, tactical execution, strategic planning, and cross-team collaboration to deliver AI-powered products to military clients.

The Program Chief Engineer will lead the technical execution of air defense programs, focusing on developing and fielding autonomous systems. This role involves deep engagement with stakeholders, driving product development based on operational learnings, and ensuring the successful delivery of AI-powered defense capabilities.

This role is for a Program Engineer on the Air Defense team at Anduril, a defense technology company. The team builds autonomous robots for air defense, integrating various Anduril systems powered by an AI operating system. The Program Engineer will be responsible for stakeholder engagement, technical ownership, tactical execution, strategic planning, and enabling cross-team collaboration to deliver AI-driven defense capabilities. The role requires translating strategic goals into actionable plans and ensuring successful execution of initiatives.

Chief Engineer for an autonomous underwater system (Dive-XL) within a defense technology company. Responsible for technical vision, architecture, roadmap, and execution, leading a multi-disciplinary team. Focuses on system integration, performance, test & evaluation, and technical problem-solving for complex autonomous systems in challenging maritime environments.

Anduril Industries is seeking a Robotics Engineer for their Maritime Division in Sydney, Australia. The role focuses on delivering perception and planning capabilities for autonomous vehicles, involving systems analysis, sensor integration, perception architecture, motion planning, and machine learning. The engineer will own projects end-to-end, contributing to the entire product lifecycle of next-generation autonomous platforms. This includes implementing safe navigation, collision avoidance, and situational awareness systems, as well as developing scalable sub-systems and utilizing advanced techniques in computer vision, sensor fusion, and machine learning. Collaboration with cross-functional teams and testing/validation through simulation and real-world data analysis are key aspects of the job. The role requires a Bachelor's degree in a relevant field, proficiency in C++ and/or Python, and demonstrated knowledge in areas like computer vision or machine learning. Experience in a senior perception or planning role for a robotic system and the capacity to act as a technical owner are essential. The position also requires the ability to obtain an Australian Government Negative Vetting 2 security clearance.

Anduril Industries is seeking a Robotics Engineer for their Maritime Division in Sydney, Australia. The role focuses on delivering perception and planning capabilities for autonomous vehicles, involving systems analysis, sensor integration, perception architecture, motion planning, and machine learning. The engineer will own projects end-to-end, contributing to the entire product lifecycle of next-generation autonomous platforms. This includes implementing safe navigation, collision avoidance, and situational awareness systems, as well as developing scalable sub-systems and utilizing advanced techniques in computer vision, sensor fusion, and machine learning. Collaboration with cross-functional teams and testing/validation through simulation and real-world data analysis are key aspects of the job. The role requires a Bachelor's degree in a relevant field, proficiency in C++ and/or Python, and demonstrated knowledge in areas like computer vision or machine learning. Experience in a senior perception or planning role for a robotic system and the capacity to act as a technical owner are essential. The position also requires the ability to obtain an Australian Government Negative Vetting 2 security clearance.

Robotics Engineer for Anduril's Maritime Division, focusing on developing and delivering trusted safe navigation, collision avoidance, and situational awareness systems for autonomous maritime vehicles. The role involves implementing scalable sub-systems, utilizing advanced techniques in computer vision, sensor fusion, and machine learning, and conducting thorough testing and validation. This position requires end-to-end ownership of projects throughout the product life-cycle, collaboration with cross-functional teams, and potentially mentoring junior members.

This role focuses on developing and integrating perception and planning capabilities for autonomous maritime vehicles. It involves end-to-end ownership of robotic systems, utilizing advanced techniques in computer vision, sensor fusion, and machine learning, and ensuring safe navigation and collision avoidance. The engineer will contribute to reusable software components and collaborate with cross-functional teams for system integration and testing.

Robotics Engineer for Anduril's Maritime Division, focusing on developing and delivering trusted safe navigation, collision avoidance, and situational awareness systems for autonomous maritime vehicles. The role involves implementing scalable sub-systems, utilizing advanced techniques in computer vision, sensor fusion, and machine learning, and conducting thorough testing and validation. This position requires end-to-end ownership of projects throughout the product life-cycle, collaboration with cross-functional teams, and potentially mentoring junior members.

Robotics Software Engineer role focused on developing and deploying multi-asset autonomy systems for defense applications. The role involves networking, autonomy, systems integration, and ensuring seamless operation of autonomous systems. It requires strong C++ or Rust skills and experience with data processing, complex systems, and real-world deployments.

Robotics Software Engineer at Anduril Industries, focusing on developing autonomous drone systems and integrating AI-powered operating systems. The role involves building core robotics libraries, simulators, optimizing performance, and contributing to multi-agent coordination systems for UAVs. Requires C++ or Rust proficiency, Linux development, and experience with deployed systems.

Software Engineer role focused on developing core libraries and services for collaborative aerial robotic systems, including motion deconfliction and contingency management. The role involves feature development for products like unmanned fighter jets and cruise missiles, working closely with hardware teams and operational experts. Experience with C++/Rust in a Linux environment is required, with preferred experience in motion planning, perception, localization, and multi-agent coordination of UAVs.

Software Engineer role focused on developing core libraries and services for collaborative aerial robotic systems, including motion deconfliction and contingency management. The role involves feature development for products like unmanned fighter jets and cruise missiles, working closely with hardware teams and operational experts. Experience with C++/Rust in a Linux environment is required, with preferred experience in motion planning, perception, localization, and multi-agent coordination of UAVs.

Software Engineer role focused on building autonomy software stacks for aerial and multi-domain robotic systems, including computer vision, motion planning, SLAM, controls, and estimation. The role involves developing multi-agent autonomous systems and integrating them into flight systems.

Senior DSP Engineer role at Anduril, a defense technology company, focusing on optimizing DSP and ML algorithms for FPGAs/GPUs, developing software-defined radios, and designing algorithms for RADAR systems. Requires experience with DSP implementation, Python/MATLAB, embedded devices, and familiarity with deep learning algorithms.

This role focuses on the flight testing and evaluation of mission autonomy systems for defense technology. The Senior Flight Test Engineer will plan, coordinate, and execute system-level testing of hardware and software, with an emphasis on developmental testing of flight systems. Responsibilities include requirements development, test planning and execution, data analysis, and safety/risk assessment for unmanned aerial systems (UAS) and weapon systems. The role requires strong engineering fundamentals, experience with flight test programs, and the ability to work with complex autonomous systems.

Anduril Industries is seeking a Senior Flight Test Engineer focused on Mission Autonomy for their UAS (Unmanned Aerial Systems). The role involves driving testing methodologies for autonomous systems, designing and implementing test plans, analyzing test data to refine autonomy algorithms, and collaborating with cross-functional teams. The position requires a strong background in flight testing of autonomous or remotely piloted systems and experience with simulation environments.

Seeking a Senior Guidance, Navigation & Control (GNC) Engineer to develop, test, and implement GNC systems and architectures for aerospace programs including missiles and UAVs. The role involves algorithm development, simulation, and collaboration within a multidisciplinary team, focusing on autonomous safety-critical systems for defense applications.

The Senior Guidance, Navigation & Control (GNC) Engineer will lead the design, development, testing, and implementation of navigation systems for autonomous aerospace vehicles, including subsonic, supersonic, and hypersonic systems. This role involves integrating advanced sensor fusion algorithms, developing navigation filters (like Extended Kalman filters), and ensuring navigation performance in complex environments. The position requires expertise in inertial navigation, GNSS, and real-time systems, with a focus on defense technology.

Senior Machine Vision Engineer for manufacturing automation at a defense technology company. Develop and implement machine vision for automation, quality inspection, and defect detection. Collaborate with cross-functional teams and lead efforts in root cause analysis. Requires experience with vision system platforms, Python/C++, OpenCV, and industrial automation. Familiarity with AI-based vision systems is a plus.

Senior Software Engineering Manager at Anduril, a defense technology company, leading teams to deliver software for autonomous maritime systems. Responsibilities include roadmap design, architecture, managing development processes, team building, and budget/risk management for software integrated into products like underwater vessels. The role focuses on end-to-end ownership of software for integrated product families.

Senior Software Engineering Manager to lead teams in developing and delivering software for autonomous robotic systems in the defense technology sector. The role involves end-to-end ownership of software for integrated product families, including autonomy, simulation, data processing, and command and control. Responsibilities include roadmap planning, architecture design, team management, and process improvement, with a focus on delivering cutting-edge AI and robotics solutions.

Senior Manager, Software Engineering for Anduril's Maritime Division, focusing on leading teams to deliver software for autonomous maritime systems. Responsibilities include roadmap development, architecture design, team management, and end-to-end product lifecycle ownership. The role involves managing software for autonomy, simulation, data processing, and command and control, with a strong emphasis on integrating AI, computer vision, and sensor fusion into defense technology products.

Senior Software Engineer for Anduril's defense technology company, focusing on vehicle software for autonomous robotics systems like unmanned fighter jets. The role involves building foundational vehicle software stacks for control, networking, sensor integration, and telemetry, supporting initiatives from simulation to live operations and fleet management. Experience with multi-agent autonomous systems and real-world deployment is preferred.

Senior Program Chief Engineer for Anduril's Air Defense team, focusing on building autonomous robots for defense applications. The role involves stakeholder engagement, technical ownership, tactical execution, strategic planning, and cross-team collaboration to deliver AI-powered defense systems.

Senior Program Chief Engineer for International Programs at Anduril, a defense technology company. The role focuses on integrating Anduril's AI-powered systems, including autonomous robots and computer vision capabilities, into international defense applications. The position requires strong technical leadership, stakeholder engagement, and the ability to translate strategic goals into actionable project plans for delivering advanced defense technology.

Anduril Industries is a defense technology company building advanced autonomous systems for military applications. This Senior Robotics Engineer role focuses on developing and integrating perception and planning capabilities for these systems, utilizing computer vision, sensor fusion, and machine learning. The role involves end-to-end ownership of subsystems, collaboration with cross-functional teams, and ensuring safe navigation and situational awareness. Experience in C++/Python, autonomous vehicle hardware, and a senior role in perception or planning is required, with a focus on delivering robotic systems.

Anduril Industries is a defense technology company building advanced autonomous systems for military applications. This Senior Robotics Engineer role focuses on developing and integrating perception and planning capabilities for these systems, utilizing computer vision, sensor fusion, and machine learning. The role involves end-to-end ownership of subsystems, collaboration with cross-functional teams, and ensuring safe navigation and situational awareness. Experience in C++/Python, autonomous vehicle hardware, and a senior role in perception or planning is required, with a focus on delivering robotic systems.

Anduril Industries is a defense technology company seeking a Senior Robotics Engineer for their Maritime Division. The role focuses on developing and delivering autonomous vehicle perception and planning capabilities, including safe navigation, collision avoidance, and situational awareness. Responsibilities involve systems analysis, sensor integration, perception architecture, motion planning, and collaboration with cross-functional teams. The position requires experience in C++/Python, familiarity with autonomous vehicle hardware, and demonstrated knowledge in computer vision, sensor fusion, SLAM, motion planning, or machine learning. Experience in a senior perception or planning role for a robotic system and the ability to act as a technical owner are essential. The role involves working with advanced techniques in computer vision, sensor fusion, and machine learning to enhance vehicle capabilities and requires the ability to obtain a U.S. Secret security clearance.

Anduril Industries is a defense technology company building autonomous maritime systems. This Senior Robotics Engineer role focuses on designing and implementing perception and planning capabilities for these systems, utilizing AI, computer vision, and sensor fusion. The role involves end-to-end ownership of subsystems, collaboration with cross-functional teams, and ensuring safe navigation and situational awareness. Experience with autonomous vehicle hardware, software development in C++/Python, and a background in robotics or a related field are required. The position is based in Costa Mesa, CA, with a salary range of $220,000-$292,000 USD and requires eligibility for a U.S. Secret security clearance.

Anduril Industries is a defense technology company seeking a Senior Robotics Engineer for their Maritime Division. The role focuses on developing and delivering autonomous vehicle perception and planning capabilities, including safe navigation, collision avoidance, and situational awareness. Responsibilities involve systems analysis, sensor integration, perception architecture, motion planning, and collaboration with cross-functional teams. The position requires experience in C++/Python, familiarity with autonomous vehicle hardware, and demonstrated knowledge in computer vision, sensor fusion, SLAM, motion planning, or machine learning. Experience in a senior perception or planning role for a robotic system and the ability to act as a technical owner are essential. The role involves working with advanced techniques in computer vision, sensor fusion, and machine learning to enhance vehicle capabilities and requires the ability to obtain a U.S. Secret security clearance.

This role focuses on designing and implementing perception and planning capabilities for autonomous maritime vehicles. It involves systems analysis, sensor integration, and leveraging advanced techniques in computer vision, sensor fusion, and machine learning to enhance vehicle capabilities. The engineer will have end-to-end ownership of subsystems and contribute to the entire product lifecycle of next-generation autonomous platforms.

Anduril Industries is hiring a Senior Robotics Engineer for their Maritime Division. The role focuses on designing and implementing perception and planning capabilities for autonomous maritime vehicles, utilizing advanced techniques in computer vision, sensor fusion, and machine learning. Responsibilities include end-to-end ownership of subsystems, stakeholder engagement, and technical leadership.

Senior Robotics Software Engineer role focused on developing and deploying multi-asset autonomy systems for defense applications. The role involves owning mission autonomy systems, writing code to improve products, collaborating across teams, and analyzing metrics. It requires strong C++ or Rust experience, data processing skills, and the ability to navigate complex systems. Experience with multi-agent autonomous systems and behavior trees is preferred.

Senior Robotics Software Engineer at Anduril Industries, a defense technology company, focusing on developing and implementing advanced autonomous systems and robotics. The role involves core robotics libraries, simulation, performance optimization, and multi-agent coordination for UAVs, contributing to the entire product lifecycle from concept to deployment.

Senior Robotics Software Engineer at Anduril, a defense technology company, focusing on developing foundational vehicle software for autonomous robotics systems. The role involves writing core libraries for collaborative robots, owning feature development, and working with hardware and operational teams. Requires C++ or Rust experience, understanding of algorithms, and ability to obtain a Top Secret security clearance. Experience in motion planning, perception, and multi-agent coordination is preferred.

This role focuses on developing discrimination algorithms for EO/IR sensors in space and missile defense. The engineer will design signal processing pipelines, including detection, feature extraction, and image processing, to classify threats from non-threats. The position requires expertise in signal processing, classification, detection theory, and algorithm development, with a focus on transitioning algorithms to production environments and providing technical leadership.

Senior Software Engineer at Anduril, a defense technology company, contributing to AI-powered systems for military applications. The role involves developing state-of-the-art algorithms and software, prototyping solutions, implementing high-performance software, and engaging with customers. Requires strong software engineering, machine learning, applied mathematics, and engineering fundamentals, with experience in C/C++, Python, Matlab, and big data technologies. Must be eligible for a U.S. Top Secret SCI security clearance.

Senior Software Engineer at Anduril Industries, a defense technology company, focusing on delivering AI-powered autonomous systems for maritime operations. The role involves end-to-end ownership of software-enabled solutions, from design and implementation to deployment and sustainment, working across the full software stack and product lifecycle.

Senior Software Engineer role at Anduril's Maritime Division, focusing on delivering end-to-end software solutions for autonomous maritime systems. Responsibilities include designing, implementing, and supporting software across the full product lifecycle, with an emphasis on autonomy, simulation, data processing, and payload integration. The role involves technical leadership, stakeholder engagement, and mentoring junior engineers, contributing to reusable components for various Anduril product lines.

Senior Software Engineer at Anduril Industries focused on building autonomous robotics systems for defense applications. The role involves developing core robotics libraries, implementing features like Software-in-the-Loop simulators, optimizing performance, and contributing to multi-agent coordination systems for UAVs. Requires strong C++/Rust skills, experience in Linux, and a background in robotics or related fields.

Senior Software Engineer at Anduril Industries, a defense technology company, focusing on developing and deploying AI-powered autonomous systems for maritime operations. The role involves end-to-end ownership of software-enabled capabilities, from design and implementation to deployment and sustainment, working within a multi-disciplinary team to deliver advanced military capabilities.

Senior Software Engineer at Anduril, a defense technology company, contributing to an AI-powered operating system (Lattice OS) that transforms military capabilities. The role involves developing state-of-the-art algorithms and software, prototyping solutions, implementing high-performance software, and working with customers. Requires 8+ years of experience, C/C++, Python, big data, software engineering principles, machine learning (supervised/unsupervised), applied mathematics, and engineering fundamentals (controls, estimation, DSP). Must be eligible for U.S. Top Secret SCI clearance.

Senior Software Engineer for Anduril's Air Defense team, focusing on developing and deploying networked robots and systems for detecting and neutralizing aerial threats. The role involves software solutions for networking, autonomy, systems integration, and robotics, with a focus on delivering critical capabilities to military customers.

Senior Software Engineer for Anduril's Tactical Recon & Strike (TRS) division, focusing on building autonomous drones and solid rocket motors. The role involves developing software for autonomous systems, including hand controllers, sensors, computer vision, and state machines, contributing to the entire product lifecycle from concept to deployment. Requires C++ or Rust experience and eligibility for a US Secret security clearance.

Senior Software Engineer for Anduril's Tactical Recon & Strike division, focusing on building autonomous drones and solid rocket motors. The role involves developing core robotics libraries, implementing features like target tracking pipelines, and collaborating across hardware and manufacturing teams. Requires C++ or Rust proficiency, experience in robotics, and eligibility for a U.S. Secret security clearance.

Senior Software Engineering Manager for a defense technology company, leading teams to develop hardware and software UAV solutions. The role involves defining strategy, strengthening engineering capabilities, executing customer programs from R&D to production, and managing a portfolio of software-driven programs. Requires deep understanding of autonomous robotics systems and experience in rigorous software development and delivery.

Senior Software Engineer for Anduril's Maritime Division, focusing on developing and delivering end-to-end software solutions for autonomous maritime platforms. This role involves driving the delivery of software for autonomy, simulation, data processing, and command and control, with a strong emphasis on customer deployment and lifecycle ownership.

Senior Software Engineer for Anduril's Maritime Division, focusing on developing and delivering end-to-end software solutions for autonomous maritime platforms. This role involves driving the delivery of software for autonomy, simulation, data processing, and command and control, with a strong emphasis on customer deployment and lifecycle ownership.

Senior Software Engineer specializing in Computer Vision and Machine Learning Engineering for autonomous drones and defense technology. Focus on object detection, object tracking, and integrating classical computer vision with ML methods for UAV perception systems.

Senior Software Engineer for the Air Defense team at Anduril, focusing on robotics, autonomy, systems integration, and AI/computer vision for defense systems. The role involves developing core libraries, owning feature development, and implementing scalable sub-systems for robots that detect and neutralize aerial threats. Requires strong C++/Rust experience, leadership skills, and eligibility for Top Secret SCI clearance.

Senior Software Engineer for Anduril's defense technology division, focusing on building autonomous drones and related systems. The role involves developing core robotics libraries, implementing features like simulators, optimizing performance, integrating software with hardware, and contributing to multi-agent coordination systems for UAVs. Requires strong C++/Rust, Linux, and robotics expertise, with a focus on autonomy and system integration.

Senior Software Engineer role at a defense technology company focused on building and evolving complex software systems for real-time applications, including target tracking, sensor fusion, and state estimation. The role involves architecting, prototyping, and deploying high-performance Rust software, with a strong emphasis on applied mathematics, signal processing, and estimation theory. While AI/ML is mentioned as a component, the primary focus is on the engineering and deployment of these systems.

Senior Software Engineer role focused on state estimation and target tracking for defense technology. Involves prototyping, deploying, and optimizing algorithms for real-time systems, sensor fusion, and probabilistic reasoning. Requires strong programming skills in C++, Python, and Matlab, with knowledge of Kalman filters, Bayesian filtering, and applied mathematics. Experience with machine learning applied to tracking and recognition is also required.

Senior Systems Integration and Test Engineer for a defense technology company building autonomous maritime platforms. The role involves designing, integrating, and testing various subsystems (sensors, navigation, autonomy software, etc.) into surface platforms, ensuring system performance, and supporting product roadmaps. The company uses an AI-powered operating system and focuses on autonomy, computer vision, and sensor fusion.

Senior Systems Engineer at Anduril, a defense technology company, focusing on developing unmanned systems with unsupervised autonomy. The role involves owning technology solutions deployed to customers, acting as a subject matter expert in areas like robotic perception and cybersecurity, and designing/architecting integrated systems for autonomous vehicles. This position requires extensive experience in engineering, particularly with robotic and autonomous systems, and the ability to manage complex systems throughout their lifecycle.

Senior Systems Engineer role at a defense technology company, focusing on leading the technical execution of autonomous drone systems from concept to production. The role involves system architecture, design, testing, and cross-functional team leadership, with a requirement for a U.S. Secret security clearance.

Senior Software Engineer focused on developing advanced 2D/3D tracking algorithms for space objects, processing sensor data into actionable tracks for space situational awareness. This role involves architecting multi-target tracking systems, state estimation, data association, physics-based modeling, and mentoring engineers, with a focus on transitioning algorithms from prototypes to production C++ code.

Senior Software Engineer focused on developing advanced 2D/3D tracking algorithms for space object custody, processing sensor data into actionable tracks. This role involves architecting and implementing multi-target tracking systems using state estimation and data association techniques, developing physics-based models for validation, and mentoring engineers. The engineer will transition algorithms from prototypes to production C++ code for operational systems within a defense technology company.

Develops discrimination algorithms for EO/IR sensors to classify threats in space and missile defense missions, involving signal processing pipelines, decision logic, and algorithm optimization. Collaborates with software engineers for production deployment and engages with customers.

Software Engineer role focused on designing and implementing advanced tracking algorithms and real-time software systems for air and missile defense, processing radar sensor data to track multiple targets. The role involves building and leveraging simulation environments, optimizing for performance-critical scenarios, and integrating solutions into larger defense systems. Experience with C++, Python, mathematics, and software engineering fundamentals is required, with desired experience in tracking algorithms, sensor fusion, HPC, and machine learning.

Software Engineer at Anduril Industries, a defense technology company, contributing to the development of AI-powered systems for military applications. The role involves prototyping, implementing high-performance software, and working with machine learning, applied mathematics, and engineering principles. Requires C/C++, Python, Matlab, big data technologies, and eligibility for a Top Secret SCI security clearance.

Software Engineer for the Air Defense team at Anduril, focusing on building robots that detect and neutralize aerial threats. The role involves developing software for networking, autonomy, systems integration, and robotics, contributing to an AI-powered operating system (Lattice OS) that integrates various data streams for command and control. The engineer will own software solutions deployed to customers, improve products, scale capabilities, and collaborate across teams to deliver critical mission outcomes.

Software Engineer for Anduril's Air Defense team, focusing on building and deploying robotic systems that detect and neutralize aerial threats. The role involves developing software for networking, autonomy, systems integration, and robotics, with a strong emphasis on delivering mission-critical capabilities in real-world environments.

Software Engineer to build and enhance Anvil, an autonomous kinetic interceptor for defeating aerial threats. The role involves writing robotics software, owning feature development, and integrating with other defense systems within the Anduril Lattice ecosystem. Requires C++ or Rust experience and a strong engineering background in robotics or related fields. Experience with motion planning, perception, or controls is preferred.

Software Engineer role at Anduril, a defense technology company, focusing on building and deploying AI-powered software solutions for military capabilities. The role involves owning software solutions, writing code for product improvement and scaling, collaborating across teams, analyzing metrics, triaging issues, and partnering with end-users. Requires an active US Secret Clearance and experience in software development with significant data processing and analysis.

Software Engineer role focused on developing and implementing core robotics libraries, simulators, and features for autonomous drones and other robotic systems. The role involves optimizing performance, integrating software with hardware, troubleshooting deployed systems, and contributing to multi-agent coordination. It requires strong C++/Rust skills, experience in Linux, and a willingness to work in a defense technology environment.

Software Engineer role at a defense technology company focused on building and deploying autonomous maritime systems. The role involves end-to-end ownership of software-enabled solutions, contributing to the development of next-generation autonomous platforms, and working with AI, computer vision, and sensor fusion technologies. The position requires a Bachelor's degree, software engineering experience, and the ability to obtain a security clearance.

Software Engineer on the Maneuver Dominance team at Anduril, focusing on building operationally relevant, multi-asset autonomy. This role involves developing software services and autonomy algorithms for autonomous capabilities, integrating platforms, and ensuring seamless operation of Anduril products. Responsibilities include feature development, code improvement, cross-team collaboration, metrics analysis, issue triage, and working with hardware and operational teams. The role requires strong C++ or Rust experience, data processing skills, and the ability to navigate complex systems, with a focus on delivering real-world impact in the defense sector.

Software Engineer specializing in Robotics for the Air Defense team at Anduril, a defense technology company. The role involves developing and integrating systems for robots that detect and neutralize aerial threats, focusing on autonomy, AI, computer vision, sensor fusion, and networking. Responsibilities include writing core libraries, owning feature development, implementing sub-systems like perception and motion planning, and working with hardware teams. Requires 3+ years of C++/Rust experience, Linux development, and leadership potential. Experience with embedded systems, motion planning, perception, and sensor analysis is preferred. The role requires eligibility for a U.S. Top Secret security clearance.

Software Engineer specializing in Robotics for the Air Defense team, focusing on developing and integrating systems for robots that detect and neutralize aerial threats. The role involves core robotics functions like frame transformations, targeting, guidance, perception, motion planning, and system integration, with a strong emphasis on delivering mission-critical capabilities in a defense technology context.

Staff Flight Test Engineer focused on mission autonomy for UAS (Unmanned Aerial Systems) in the defense sector. Role involves designing, implementing, and analyzing tests for autonomous systems, collaborating with cross-functional teams, and driving end-to-end test management. Requires significant experience in flight testing autonomous systems and strong analytical skills.

Staff Robotics Engineer role focused on delivering vehicle perception and planning capabilities for autonomous defense systems. This involves leading technical aspects, hands-on implementation, and end-to-end ownership of safe and effective vehicle autonomy throughout the product lifecycle. Responsibilities include architecting, designing, and implementing navigation, collision avoidance, situational awareness, sensor suites, perception algorithms, and planning algorithms, utilizing computer vision, sensor fusion, and machine learning. The role also involves testing, validation, and collaboration with cross-functional teams.

Staff Robotics Engineer role focused on delivering vehicle perception and planning capabilities for autonomous defense systems. This involves leading technical aspects, hands-on implementation, and end-to-end ownership of safe and effective vehicle autonomy throughout the product lifecycle. Responsibilities include architecting, designing, and implementing navigation, collision avoidance, situational awareness, sensor suites, perception algorithms, and planning algorithms, utilizing computer vision, sensor fusion, and machine learning. The role also involves testing, validation, and collaboration with cross-functional teams.

Staff Robotics Engineer focused on delivering vehicle perception and planning capabilities for autonomous maritime systems. This role involves leading technical delivery, hands-on implementation, and end-to-end ownership of safe and effective vehicle autonomy throughout the product lifecycle, utilizing advanced techniques in computer vision, sensor fusion, and machine learning.

Staff Robotics Engineer focused on delivering perception and planning capabilities for autonomous maritime vehicles. This role involves leading technical delivery, hands-on implementation, systems analysis, sensor integration, and ensuring the safety and effectiveness of vehicle autonomy throughout the product lifecycle. The engineer will utilize advanced techniques in computer vision, sensor fusion, and machine learning, and conduct testing and validation using simulation and real-world data.

Staff Robotics Engineer focused on delivering vehicle perception and planning capabilities for autonomous maritime systems. This role involves leading technical delivery, hands-on implementation, and end-to-end ownership of safe and effective vehicle autonomy throughout the product lifecycle, utilizing advanced techniques in computer vision, sensor fusion, and machine learning.

Staff Robotics Software Engineer focused on air vehicle autonomy, developing core libraries and services for collaborative robot teams, owning feature development for products like unmanned fighter jets, and working closely with hardware and operational experts. The role involves integrating sensor systems, perception, and decision-making for autonomous systems in a defense context.

Staff Robotics Software Engineer focused on air vehicle autonomy, developing core libraries and services for collaborative robot teams, owning feature development for products like unmanned fighter jets, and working closely with hardware and operational experts. The role involves integrating sensor systems, perception, and decision-making for autonomous systems in a defense context.

Staff Software Engineer at Anduril Industries, a defense technology company, focusing on leading the delivery of software for autonomous systems. The role involves technical leadership, end-to-end ownership of software roadmaps, architecting robotic systems, and contributing to the development of software inputs for autonomous platforms. This includes on- and off-platform software, testing, simulation, and mentoring.

Staff Software Engineer role at Anduril Industries, a defense technology company, focusing on the delivery of software for autonomous systems. The role involves leading the design, development, and lifecycle management of software for robotic platforms, including autonomy, simulation, data processing, and command and control. It requires strong technical leadership, end-to-end ownership, and collaboration across multiple teams and stakeholders, with a focus on delivering advanced AI and robotics capabilities for maritime operations.

Staff Software Engineer role focused on architecting, designing, and delivering software for autonomous maritime systems, including autonomy, simulation, data processing, and command and control. The role involves end-to-end ownership, edge deployment in constrained environments, and leading teams to build and evolve next-generation platforms.

Staff Software Engineer for Anduril's Air Defense team, focusing on building and deploying software solutions for robots that detect and neutralize aerial threats. The role involves networking, autonomy, systems integration, and robotics, with a focus on delivering critical software for defense applications.

Staff Software Engineer for Anduril's Tactical Recon & Strike division, focusing on developing autonomous drones and related systems. The role involves core robotics libraries, simulation, performance optimization, systems integration, and multi-agent coordination for UAVs. Requires strong C++/Rust, Linux, and experience with complex robotics problems in a defense technology context.

Staff Software Engineer role focused on leading the delivery of software for autonomous maritime systems, including autonomy, simulation, data processing, and command and control. The role involves end-to-end ownership of the software product lifecycle, from architecture and design to delivery and evolution, with a strong emphasis on integrating AI, computer vision, and sensor fusion technologies into defense products.

Staff Software Engineer role at Anduril, a defense technology company, focusing on leading the delivery of software for autonomous maritime systems. The role involves owning the software roadmap, driving architecture and design for robotic systems, and contributing to the development of software inputs for autonomous systems. It requires extensive experience in software engineering, systems design, and leadership, with a focus on end-to-end outcome ownership throughout the product lifecycle.

Staff Software Engineer role focused on leading the delivery of software for autonomous maritime systems, including autonomy, simulation, data processing, and command and control. The role involves end-to-end ownership of the software product lifecycle, from architecture and design to delivery and evolution, with a strong emphasis on integrating AI, computer vision, and sensor fusion technologies into defense products.

Staff Software Engineer specializing in Robotics for Anduril's Air Defense team. The role involves developing and integrating systems for collaborative robot teams, focusing on autonomy, AI, computer vision, sensor fusion, and networking for defense applications. Responsibilities include core library development, feature ownership, and implementing sub-systems like perception, motion planning, and anomaly detection. Requires strong C++/Rust experience, leadership skills, and eligibility for Top Secret SCI clearance.

Staff Software Engineer for Anduril's Maritime team, focusing on designing and developing core decision-making and autonomy software for autonomous underwater vehicles (AUVs). The role involves leading architecture, implementation, and deployment of logic for environmental understanding, navigation, threat response, and complex mission execution. It requires technical leadership, hands-on contributions, roadmap management, customer engagement, and owning the development of mission systems and core robotics libraries.

Systems Engineer role focused on end-to-end hardware product development for defense technology, integrating AI and computer vision for autonomous awareness systems. Responsibilities include defining system requirements, leading integration of new capabilities, and ensuring scalable, production-ready solutions for military applications.

Systems Software Engineer at Anduril, a defense technology company, focusing on designing, integrating, and managing complex, software-intensive mission autonomy systems for ASVs. The role involves bridging hardware and software, managing the entire lifecycle from ConOps to maintenance, and ensuring the effectiveness and reliability of autonomous maritime systems.

The role involves operating and supporting autonomy-enabled UAVs, bridging product engineering and deployed operations. Responsibilities include ensuring mission success in austere environments, shaping product deployment and sustainment, and supporting vehicle autonomy development through test events and customer demonstrations. The role requires hands-on technical experience, prior military/defense contractor experience, understanding of flight operations and aircraft systems, and problem-solving in unstructured situations. Experience with programming languages (Python, Rust, MATLAB), IP networking, and radios is also expected. Preferred qualifications include experience with autonomy (Behavior Trees, CV models, multi-vehicle operation).

Salesforce is seeking a Principal Agentic Data Systems Engineer to architect and manage a private ecosystem of autonomous agents for ETL, synthetic data generation, automated QA, and predictive modeling. This role involves designing multi-step reasoning architectures, verification protocols, and managing hand-off protocols between specialized AI agents, acting as a central anchor for a hybrid human-agent intelligence unit. The engineer will also develop and maintain Model Context Protocol (MCP) servers for agent access to data sources.

Salesforce AI Research is seeking an AI Research Scientist/Engineer to develop new technology and science for millions of CRM customers, focusing on large-scale Generative AI, Agentic Systems, Speech Intelligence, and Multimodal Deep Learning. The role involves discovering research problems, developing novel models, and bridging theory with customer-facing reality, with opportunities to advance state-of-the-art AI and see work operate at massive scale within an enterprise context. Responsibilities include owning research goals, developing novel models and solutions for enterprise problems, and designing/building production-ready services and agentic evaluators.

Salesforce is seeking an AI/ML Engineer to join their Agentic AI team, focusing on Data Management and building scalable AI solutions like Agents, AI Copilots, Chatbots, AI Planners, and RAG solutions. The role involves technical leadership, architectural guidance, and driving the full SDLC for Agentic AI products within an enterprise context.

Salesforce AI Research is seeking outstanding research interns to collaborate on projects leading to top-tier conference submissions. The role involves developing novel algorithms in NLP, CV, RL, or general ML, with a focus on pure research aligned with PhD areas. Candidates should have a strong background in deep learning and experience with libraries like PyTorch or TensorFlow.

Machine Learning Engineer to build next-generation agentic AI platforms, working with Data Scientists, Software Engineers, and product managers to design, implement, and iterate agentic AI systems. The role involves innovating at the frontier of the field to create new solutions and define new product categories with significant customer impact.

Senior AI/ML Engineer at Salesforce focusing on the Agentic AI team, specifically for Data Management. The role involves developing, implementing, and delivering scalable Agentic AI services like Agents, Copilots, Chatbots, AI Planners, and RAG solutions. It requires leading design and quality strategies for data services, analyzing technical feasibility, driving long-term design strategies, and collaborating with cross-functional teams. The position also involves troubleshooting production issues and acting as a domain expert.

Lead Agentic Data Systems Engineer responsible for architecting and maintaining a private ecosystem of 10+ autonomous agents for ETL, synthetic data generation, automated QA, and predictive modeling. The role involves designing multi-step reasoning architectures, verification protocols, and governance for agents, as well as developing MCP servers for data access. Requires strong Python, SQL, dbt, Airflow, Spark, Snowflake, and agentic framework expertise.

Software Engineer role focused on building the AI Platform at Slack, enabling product teams to integrate AI features. This involves developing developer tooling, SDKs, CI/CD pipelines, and evaluation frameworks for AI agents and LLMs, with a focus on self-service and reliability. The role also involves managing cloud AI services and ensuring AI quality and safety.

Software Engineer role focused on building and operating foundational ML infrastructure for Slack AI. This includes systems for large-scale model training, GPU-backed inference, and deployment using Kubernetes, Ray, and vLLM. The role emphasizes reliability, performance, and scalability for AI-driven capabilities within Slack.

The Field CTO will lead the technical vision for strategic global accounts, focusing on expanding Agentforce for Supply Chain and the broader Agentic Process Automation suite. This role involves bridging legacy systems with autonomous intelligence, acting as a trusted advisor to C-suite executives, and translating complex agentic process automation into scalable business outcomes. Responsibilities include architecting the "Agentic Stack", partnering with product and engineering, designing frameworks for navigating IT landscapes, providing high-stakes technical advisory, leading value engineering and prototyping, and acting as a bridge between field requirements and product development.

Salesforce is seeking early-career AI Builders to design, develop, and deploy agentic solutions for Fortune 500 companies. This role involves building AI agents that take real actions, designing agent intelligence (prompts, reasoning, tool calls), supporting the technical lifecycle, and collaborating with clients to create agentic solutions. The program emphasizes hands-on technical skill development, mentorship, and real-time customer impact.

Software Engineer role focused on building internal AI-powered productivity tools and agentic experiences to solve performance problems for engineering teams. Responsibilities include developing AI agents for triaging issues, automating performance analysis, and instrumenting systems to measure AI agent performance. Requires strong software engineering fundamentals, ML/AI knowledge (LLMs, NLP, inference, fine-tuning, agentic workflows), and Python experience.

Salesforce is seeking an AI Technical Architect to lead enterprise AI transformation initiatives, focusing on designing, deploying, and scaling intelligent Agentforce solutions. The role involves owning end-to-end technical architecture for agent ecosystems, including orchestration models, tool integrations, reasoning flows, and multi-agent patterns, as well as advising customers and guiding delivery execution. Experience with Salesforce implementations, agentic systems, and data foundations for AI is required.

Salesforce is seeking early-career AI Builders to join their Agentforce program. This role involves designing, developing, and deploying agentic AI solutions for enterprise clients, working within cross-functional teams to deliver real-time customer impact. The position emphasizes a builder mindset and hands-on experience with AI tools and development lifecycles.

Salesforce is seeking a Senior Product Manager to own a core area of Agentforce Authoring, a platform for building, evaluating, and managing AI-powered agents. The role requires a hands-on approach, fluency with coding agents, and a track record of shipping products for technical users. The PM will own the roadmap, define success metrics, prototype ideas, dogfood the product, and collaborate across engineering, design, and other PMs to ship and iterate on agent authoring experiences.

Salesforce is seeking a Partner Technical Architect to help SI partners build and scale production-grade Agentforce solutions. The role involves prototyping, building reference implementations, reviewing partner architectures, and coaching partners. The ideal candidate has strong engineering judgment, applied AI fluency, and experience with LLMs, agents, RAG, and tool use, with a focus on enterprise architecture and production readiness in regulated environments.

Senior Engineering contributor on the Agentforce platform team, owning the architecture, design, and execution of the Agentic AI platform and applications. Collaborates with software engineers, data scientists, product managers, and data teams to build and turn cutting-edge architecture and research into scalable, production-ready systems. Focuses on backend systems, data pipelines for training and inference, translating user needs into technical requirements, setting technical direction, mentoring engineers, and driving ML best practices.

Salesforce is seeking a Senior/Lead AI Software Engineer to join their Agentforce for Supply Chain team. This role will focus on building and architecting intelligent agents that automate complex supply chain tasks. The engineer will lead the development of planning systems, distributed systems, and ensure seamless integration of AI agents into human workflows. The position requires strong software engineering skills, experience with AI orchestration frameworks, and a focus on production-grade software development.

Salesforce AI Research is seeking a Machine Learning Engineer to develop a next-generation agentic AI platform. The role involves designing, implementing, and iterating on agentic AI systems, integrating them into human workflows, and contributing to the shared system context. The position requires strong engineering skills, deep ML knowledge, and experience with LLMs, agentic workflows, and production-grade AI systems.

This role focuses on deploying and validating new agentic CCaaS features with enterprise customers, identifying platform gaps, and building reusable assets to shape the product roadmap. It involves deep customer engagement, rapid prototyping, and acting as a technical advisor for AI-driven contact center solutions.

Salesforce is seeking a Senior Director, Forward Deployed Engineering Lead for their Agentforce Supply Chain team. This role involves leading a global team of engineers to work with strategic customers, validate emerging AI capabilities, harden agentic workflow infrastructure for complex manufacturing environments, and translate field insights into product roadmap priorities. The position requires strong leadership, technical expertise in AI/LLM solutions including agentic frameworks and RAG, and experience in supply chain management.

Senior/Lead Forward Deployed Engineer (FDE) for Salesforce's Public Sector team, focusing on deploying AI and transformative solutions for U.S. Department of Defense, Intelligence Community, and Aerospace clients. The role involves designing, developing, and implementing bespoke AI and LLM-based intelligent agents and automated workflows using the Agentforce platform, with a strong emphasis on hands-on coding, end-to-end technical delivery, and customer collaboration. This includes owning the data lifecycle and conducting deep-dive debugging for AI systems.

This role focuses on leading complex AI agentic deployments for enterprise clients, involving the design, development, and end-to-end technical delivery of AI solutions built on the Salesforce Agentforce platform. The engineer will architect and implement intelligent agents and automated workflows, integrate LLMs, and work with advanced orchestration frameworks, acting as a hands-on technical leader and strategic partner.

Salesforce is seeking a Principal Researcher with a specialized focus on Machine Learning to partner with executive leadership and C-suite stakeholders. The role involves setting strategic research priorities, building ML models for predictive and prescriptive workforce intelligence, and integrating advanced AI and LLMs into workforce strategy. Responsibilities include defining research questions, developing predictive and causal models, leading impact attribution studies, extracting insights from unstructured data, driving the evolution of research into scalable tools, identifying impacts on diverse employee segments, advising senior leadership, overseeing technical infrastructure and MLOps, and staying at the forefront of AI/LLM trends.