Currently tracking 440 active AI roles, down 53% versus the prior 4 weeks. Primary focus: Serve · Engineering. Salary range $100k–$575k (avg $262k).
NVIDIA currently has 496 active AI-related job listings. The majority of these roles, 52%, are focused on serving infrastructure, with agents representing another significant segment at 23%. Engineering is the dominant function, with 441 positions. The United States leads hiring geographies with 287 roles, followed by China with 64. Frequent tech tags include model_serving, inference_infra, and agent_orchestration, suggesting a focus on deployment and management of AI models. Over the last 30 days, NVIDIA posted 214 new AI roles, a 27% decrease compared to the previous 30-day period.
NVIDIA currently has 487 active AI-related roles in our index. The most common open titles are: Deep Learning Performance Architect (4), Senior Deep Learning Performance Architect (4), AI Research Scientist (3), Developer Technology Engineer - AI (3), Manager, Deep Learning Algorithms (3). Most positions are in Engineering and Research.
NVIDIA's active AI hiring is concentrated in: serving infrastructure (54%), agents (21%), application (8%). These categories follow a seven-stage AI lifecycle: data, pre-training, post-training, serving infrastructure, agents, evaluation, and application.
NVIDIA is hiring AI talent in: United States (286 roles), China (59 roles), Israel (50 roles), Germany (21 roles).
Job postings at NVIDIA most frequently reference: model serving, inference infra, agent orchestration, llm observability, multimodal.
In the past 30 days, NVIDIA has posted 110 new AI-related roles. That is a -50% change versus the prior 30 days (218 → 110).
| Title | Stage | AI score |
|---|---|---|
| Senior Scientist, Synthetic Data Generation Senior Scientist focused on synthetic data generation for training frontier LLMs, contributing to open-source libraries and advancing multimodal data generation. | DataPost-train | 10 |
| Applied Deep Learning PhD Research Intern, Reinforcement Learning for LLMs - Fall 2026 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. | Post-trainAgent |
| 10 |
| Senior Research Scientist, Multimodal Foundation Models and Robotics 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. | Post-trainAgent | 10 |
| Senior Research Scientist, Fundamental Generative AI 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. | Pretrain | 10 |
| Research Scientist, Fundamental Generative AI - New College Grad 2026 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. | Pretrain | 10 |
| Research Scientist, Fundamental Generative AI - New College Grad 2026 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. | Pretrain | 10 |
| Research Scientist, Generalist Embodied Agent Research - PhD New College Grad 2026 Research Scientist role focused on building humanoid robot foundation models and general-purpose embodied agents. Involves designing and implementing novel AI algorithms, developing large-scale training and inference methods, and deploying models in simulation and on hardware. Requires strong experience in LLMs, multimodal foundation models, reinforcement learning, agent learning, and applied robotics, with a PhD and publication record. | AgentData | 10 |
| Senior Research Scientist, Multimodal Foundation Models and Robotics Research Scientist role focused on developing multimodal foundation models and systems for general-purpose humanoid robots and embodied agents, involving algorithm design, large-scale training/inference, and deployment on physical hardware and simulations. | Post-trainAgent | 10 |
| Senior Research Scientist, Nemotron Post-training Research Scientist/Engineer at NVIDIA focused on building Nemotron models, specifically working on post-training pipelines, synthetic data, agentic RL, data/training infrastructure, and large-scale model post-training. The role involves advancing open-source foundation models, developing training data, benchmarks, LLMs, and software, and solving end-to-end foundation model post-training challenges. Requires a Master's/PhD and 5+ years of experience in model post-training, RL, and agentic systems, with experience in data curation, model training, and inference/deployment environments. | Post-trainAgent | 9 |
| High-Performance LLM Training Engineer - New College Grad 2026 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 the deep learning platform, from drivers to frameworks, and contributing to MLPerf benchmarks. | Data | 9 |
| Research Scientist, Efficient Deep Learning - New College Grad 2026 Research Scientist role focused on efficient deep learning methods, including post-training optimization, efficient architecture design, and resource-efficient training/finetuning. Requires a Ph.D. or equivalent research experience, strong Python/PyTorch skills, and experience with large-scale model training and large vision-language models. The role involves research, implementation, publication, and technology transfer. | Post-trainServe | 9 |
| Senior Scientist, Synthetic Data and Privacy Senior Scientist role focused on building LLM-based methods for synthetic data generation and privacy-preserving AI, contributing to open-source libraries within the NVIDIA NeMo ecosystem. The role involves applied research, software engineering, and optimizing LLMs for inference, with a strong emphasis on publishing original research. | DataServe | 9 |
| Senior Quantum Applied Research Scientist, Calibration and Decoding Research Scientist at NVIDIA focusing on developing AI models for quantum system calibration and decoding. This role involves building physics-informed synthetic data generation pipelines, developing surrogate models of quantum hardware, and architecting real-time AI systems. The work also includes applying reinforcement learning and online learning methods for optimization, with a strong emphasis on GPU acceleration and collaboration across Product, Engineering, and Applied Research teams to advance fault-tolerant quantum computing. | Post-trainData | 9 |
| Senior Research Manager, World Model Evaluation Lead a research team focused on world-model evaluation and benchmarking for NVIDIA's Physical AI portfolio, defining the scientific roadmap for closed-system and open-system evaluations, developing benchmarks for various physical AI capabilities, and driving evaluation-to-model-improvement loops. The role requires publishing high-quality papers and establishing rigorous standards. | Eval GatePost-train | 9 |
| Senior Systems Software Engineer, AI Stack and Performance - DGX Station Senior Systems Software Engineer focused on optimizing AI stack performance and readiness on NVIDIA's DGX Station, a workstation-class AI computer. The role involves profiling, identifying bottlenecks, and driving optimizations across the full stack from GPU kernels to applications, ensuring AI workloads like LLM inference and agents run efficiently in multi-GPU, multi-user configurations. Collaboration with framework, compiler, and GPU architecture teams is critical. | ServeShip | 9 |
| Senior Machine Learning Engineer, Perception - Autonomous Driving 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, lane structures, and other critical driving components. The engineer will also drive data-driven development, leverage simulation and augmentation, and productize solutions meeting safety and latency requirements. Experience with deep learning frameworks, Python/C++, and perception for autonomous driving or robotics is essential. | ShipData | 9 |
| Senior Software Engineer, DGX Cloud AI Infrastructure Senior Software Engineer to lead the bring-up, triage, benchmarking, analysis, and optimization of distributed training and inference workloads across NVIDIA GPU platforms at scale. This role involves setting technical direction for communication libraries, model frameworks, and inference/training stacks, leading performance and reliability investigations, defining benchmarking and qualification processes, and building resilience capabilities for large clusters. | ServePost-train | 9 |
| Software Engineer, DGX Cloud AI Infrastructure Software Engineer role focused on AI infrastructure, specifically distributed training and inference workloads on NVIDIA GPU platforms. Responsibilities include bring-up, triage, benchmarking, analysis, and optimization of these workloads at scale. Requires experience with multi-GPU/multi-node systems, debugging distributed environments, and strong Python/C++ skills. | ServePost-train | 9 |
| Senior Deep Learning Performance Architect NVIDIA is seeking a Senior Deep Learning Performance Architect to analyze and develop next-generation architectures for AI and HPC applications. The role involves developing innovative architectures, analyzing performance/cost/power trade-offs using models and simulators, understanding hardware/software interplay, and evaluating PPA for architectural decisions. Collaboration with software, product, and research teams is key. Requires MS/PhD, 6+ years experience, strong background in GPU/Deep Learning ASIC architecture for distributed training/inference, performance modeling, and ML/DL fundamentals, particularly transformer architectures. Proficiency in Python, C, C++ is essential. | Serve | 9 |
| Research Scientist, Electronic Design Automation - New College Grad 2026 Research Scientist role focused on applying AI/ML techniques, including supervised, unsupervised, reinforcement learning, and agentic AI, to Electronic Design Automation (EDA) and VLSI design. The role involves defining and conducting original research, innovating in EDA software and algorithms, and applying deep learning to improve chip design tools, with a strong emphasis on publication and collaboration. | Post-trainAgent | 9 |
| AI Inference Performance Engineer - New College Grad 2026 NVIDIA is seeking an AI Inference Performance Engineer to optimize and benchmark GenAI inference on their accelerators, working with frameworks like TensorRT-LLM, SGLang, and vLLM. The role involves driving industry benchmark results, defining cutting-edge workloads, architecting distributed inference, establishing performance methodology, and influencing the ecosystem through open-source contributions and cross-functional partnerships. Requires strong programming skills, DL framework expertise, and a deep understanding of LLM inference mechanics. | Serve | 9 |
| Senior Software Engineer, Generative AI Research NVIDIA is seeking a Senior Software Engineer for Generative AI Research to build and operate scalable infrastructure for training their world foundation model for physical AI, Cosmos. This role involves designing and developing high-throughput systems for data processing, retrieval, and workflow orchestration, improving system reliability and performance, and contributing to long-term infrastructure strategy for training, data management, and large-scale compute efficiency. The role requires a strong engineering background in distributed systems, ML infrastructure, or large-scale compute/data platforms, proficiency in Python and C++/Go/Rust, and experience with orchestration systems and data pipelines. Experience with large-scale model training infrastructure, distributed compute, synthetic data, or multimodal datasets is a plus. | DataPretrain | 9 |
| Senior Software Manager, Agentic AI Senior Software Manager to lead a team building agentic AI solutions for chip design workflows, involving coding agents, custom skills, and integration with enterprise systems. The role requires technical leadership in designing, developing, and deploying AI applications using LLMs and agentic systems, including model customization (fine-tuning, RL, instruction tuning) and overseeing retrieval/generation algorithms for enterprise data. Collaboration with cross-functional teams and ensuring high technical standards for evaluation, guardrails, and monitoring are key. | AgentPost-train | 9 |
| Senior Software Engineer - Agentic AI Senior Software Engineer role focused on leading Agentic AI solutions, including sophisticated AI agents and fine-tuning, integrating them with enterprise production systems. The role involves designing, developing, and deploying AI applications using LLMs, Agentic frameworks, and optimizing retrieval/generation algorithms for enterprise data (text, code, images) to build advanced AI applications for engineering assistants and multi-turn, multi-modal dialogue systems, ultimately solving complex problems in chip design. | AgentPost-train | 9 |
| Senior Systems Software Engineer, Machine Learning Senior Systems Software Engineer focused on Machine Learning, specifically generative AI, LLMs/VLMs, computer vision, and agentic systems. The role involves converting research into production products, building and shipping ML workflows/pipelines, and leveraging AI in data generation. Key responsibilities include defining evaluation criteria and running offline evals. Experience with multi-agent pipelines, VLMs in production, and shipping AI-powered features to users is highly valued. | AgentData | 9 |
| Senior High Performance AI Engineer Senior High Performance AI Engineer to build multi-agent systems for the CUDA ecosystem, focusing on agentic runtimes, compiler-integrated orchestration, and GPU acceleration for agent workloads like planning, tool-use, and code generation. Collaborates across the AI stack from hardware to model/agent teams. | AgentServe | 9 |
| Senior Quantum AI Research Scientist, Applied Research NVIDIA is seeking a Senior Quantum AI Research Scientist to architect and build AI solutions for fault-tolerant quantum computing, focusing on quantum error correction, decoding, calibration, and beyond. The role involves researching and developing open AI models, datasets, and benchmarks, fine-tuning models for specific quantum systems, and collaborating with cross-functional teams to integrate AI into quantum supercomputers. | Post-trainData | 9 |
| Senior Performance Architect, Nemotron NVIDIA is seeking a Senior Performance Architect for Nemotron to focus on deep model-system-hardware co-design. The role involves developing high-fidelity performance models to evaluate architectural choices, predict deployment efficiency, and ensure Pareto-optimal trade-offs for future Nemotron models. This position will guide future software and hardware roadmaps by modeling end-to-end performance impact of GenAI workflows and collaborating with research, framework, compiler, and hardware teams. | Serve | 9 |
| Software Engineer, AI and DL Kernel Libraries - New College Grad 2026 Software Engineer role focused on developing AI systems software for efficient inference, including libraries, code generators, and GPU kernels for NVIDIA's hardware. The role involves designing abstractions, optimizing kernels, building LLM serving runtimes, and contributing to open-source projects like FlashInfer and vLLM. | Serve | 9 |
| Senior Research Scientist, Post-Training LLM and DLM Senior Research Scientist focused on post-training algorithms for LLMs and DLMs, system optimization for training and serving, and developing evaluation frameworks. The role involves translating research ideas into production-ready implementations and contributing to open-source communities. | Post-trainServe | 9 |
| Senior Machine Learning Engineer - Physical AI and Synthetic Data Generation NVIDIA is seeking a Senior Machine Learning Engineer to join their Physical AI team. The role focuses on architecting and developing generative pipelines for high-fidelity synthetic data using multimodal and diffusion models. Responsibilities include building and fine-tuning large-scale models, applying user controls for data synthesis, establishing quality assurance pipelines, and leading the generation of massive training datasets. The role requires deep technical knowledge in image/video synthesis, strong programming skills, and experience in assessing synthetic data impact on model performance. | DataPost-train | 9 |
| Senior AI Security Researcher 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. | Eval GateAgent | 9 |
| Senior Software Engineer, Agentic AI – Nvidia Blueprints and NIM Integrations 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. | Agent | 9 |
| Developer Relations Manager, Higher Education and Research - AI Agents 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. | Agent | 9 |
| Senior DL Algorithms Engineer - Inference Performance 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. | Serve | 9 |
| Senior Deep Learning Software Engineer, Inference 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. | Serve | 9 |
| Senior GenAI Technical Lead, Partner Platforms 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. | AgentServe | 9 |
| Senior Solutions Architect, Autonomous Driving - GenAI 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. | AgentData | 9 |
| Senior Systems Software Engineer, Machine Learning 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. | AgentData | 9 |
| Senior AI Engineer, World Foundation Models 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. | Post-trainServe | 9 |
| Senior Research Scientist, AI-Mediated Reality and Interaction 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. | Pretrain | 9 |
| Senior AI Architect, Computer Use Agents 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. | Agent | 9 |
| Senior Machine Learning Engineer, End‑to‑End Autonomous Driving 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. | ShipData | 9 |
| Senior Research Engineer - AI Coding Tools 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. | AgentPost-train | 9 |
| Tech Engagement Lead - Model Builder 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. | ServePost-train | 9 |
| Product Manager, AI Platform SW - Agentic AI Kernel Generation 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. | AgentData | 9 |
| ML and Agentic Systems Engineer 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. | AgentEval Gate | 9 |
| Senior Software Engineer, Agentic AI 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. | AgentEval Gate | 9 |
| Principal High-Performance LLM Training Engineer 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. | PretrainPost-train | 9 |
| Senior Software Engineer, AI Inference Systems 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. | Serve | 9 |