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 Deep Learning Architect, LLM Inference 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. | Serve | 9 |
| Lead Principal Engineer, Enterprise Agentic AI Platform 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. | AgentServe |
| 9 |
| Senior Deep Learning Compiler Engineer - XLA 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. | ServePost-train | 9 |
| Principal Software Engineer - AI Inference 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. | Serve | 9 |
| Senior Research Scientist for Generative AI 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. | Post-trainPretrain | 9 |
| Senior Deep Learning Algorithm Engineer 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. | PretrainPost-train | 9 |
| Senior DL Algorithms Engineer - Inference Performance 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. | Serve | 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 various layers of the deep learning platform, including building tools for automation and contributing to MLPerf benchmarks. | Data | 9 |
| Senior Research Scientist, AI Accelerator Design and VLSI 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. | Serve | 9 |
| Senior Research Scientist, Electronic Design Automation 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. | Post-train | 9 |
| Research Scientist, AI Accelerator Design and VLSI - New College Grad 2026 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. | Serve | 9 |
| Research Scientist, Quantum Computing and AI - New College Grad 2026 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. | Data | 9 |
| Senior Applied Deep Learning Research Scientist, Efficiency 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. | Post-trainServe | 9 |
| Senior Research Scientist, Multi-Modal Language Models 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. | PretrainPost-train | 9 |
| Senior DGX Cloud AI Infrastructure Software Engineer 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. | ServePost-train | 9 |
| Agent RL Infra Engineer 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. | Post-trainAgent | 9 |
| Director of Engineering, End to End Autonomous Driving 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. | ShipPost-train | 9 |
| Director, Perception - Autonomous Vehicles 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. | ShipData | 9 |
| Senior Manager, Engineering - Enterprise AI and Automation 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. | AgentServe | 9 |
| Senior High-Performance AI Training Engineer 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. | DataServe | 9 |
| Senior Research Engineer Neural Reconstruction 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. | Post-trainServe | 9 |
| Research Scientist, AI for Graphics and Gaming - New College Grad 2026 Research Scientist role focused on Generative AI for Graphics and Gaming, involving research, training, and prototyping of AI models for real-time graphics, world models, LLM-powered game experiences, and AI-driven characters. The role emphasizes step-change research and collaboration with product, driver, and hardware teams to ship features. | Post-trainPretrain | 9 |
| Research Scientist, Human‑AI Perception and Interaction Research - PhD New College Grad 2026 Research Scientist role focused on advancing AI in areas like gaming and robotics by understanding and shaping human perception, learning, and behavior through the lens of vision science, HCI, and HRI. The role involves proposing, researching, prototyping, and testing innovative ideas, publishing at top conferences, and collaborating with researchers and product engineers. Requires a PhD or equivalent research experience and a strong publication record. | Post-train | 9 |
| Distinguished Engineer – High Performance AI Distinguished Engineer role focused on building groundbreaking agentic AI systems for the CUDA ecosystem, encompassing multi-agent runtimes, orchestration, data/evaluation pipelines, training/inference stacks, and GPU-accelerated execution. The role involves defining technical strategy, co-designing solutions with hardware/software teams, developing evaluation frameworks, and driving architecture across the AI stack. | AgentServe | 9 |
| Research Scientist, Robotics Research - PhD New College Grad 2026 Research Scientist role focused on developing and integrating algorithms, models, and methods for robotic manipulation and loco-manipulation. The role involves contributing to multi-person research projects, publishing in top conferences, collaborating with product teams for research transfer, and working with real-world robotic systems and simulation. Requires a PhD and a strong research track record in robotics, ML, or related fields, with expertise in Python, deep learning frameworks, and robotics/simulation frameworks. | AgentData | 9 |
| Research Scientist, AI-Mediated Reality and Interaction Research - PhD New College Grad 2026 Research Scientist role focused on fundamental research in AI-Mediated Reality and Interaction, involving interactive physical AIs, 4D world modeling, and human-AI interaction. The role requires proposing, researching, and prototyping innovative ideas, publishing at top conferences, and collaborating with engineers for technology transfer. Requires a Ph.D. and a strong research track record in AI and computer vision. | Pretrain | 9 |
| Research Scientist, ML Systems - PhD New College Grad 2026 Research Scientist role focused on ML Systems, contributing to hardware, software, and infrastructure for ML systems at various scales. The role involves understanding and developing solutions for efficiency, scaling, and resilience in ML systems, with a focus on co-design of algorithms and systems. Requires a PhD and expertise in areas like OS, distributed systems, inference/training systems, data management, cloud computing, or computer architecture. | ServePost-train | 9 |
| Senior Research Scientist, Efficient Deep Learning Senior Research Scientist at NVIDIA focusing on efficient deep learning methods, including post-training optimization, architecture design, and resource-efficient training/fine-tuning. The role involves research, implementation, publication, collaboration, and technology transfer to products. | Post-trainServe | 9 |
| Senior GPU Architect, Deep Learning NVIDIA is seeking a Senior GPU Architect to design and enhance GPU architecture features specifically for deep learning workloads, covering both training and inference. The role involves developing simulators, mapping deep learning algorithms to hardware, and advancing parallel computation. Requires strong C++, C++, Perl, Python programming, and a background in computer architecture and high-performance computing. | Serve | 9 |
| Senior Research Scientist, Fundamental LLM Research for Knowledge, Reasoning, and Agents NVIDIA is seeking a Senior Research Scientist to conduct fundamental LLM research, focusing on post-training, alignment, synthetic data, reasoning, novel learning paradigms, and multi-modalities. The role involves exploring new capabilities, enabling agency, acquiring commonsense knowledge, publishing research, and collaborating with product groups. | Post-trainPretrain | 9 |
| Senior Research Scientist - Autonomous Vehicles Research Scientist role focused on AI for autonomous vehicles, involving designing and implementing techniques, publishing research, and collaborating with product teams for deployment. The role emphasizes agent behavior, foundation models, closed-loop training, and AI safety within the robotics domain. | Agent | 9 |
| Senior Deep Learning Computer Architect NVIDIA is seeking a Senior Deep Learning Computer Architect to design hardware accelerator and processor architectures for next-generation platforms, enabling state-of-the-art machine learning and data analytics algorithms. The role involves analyzing deep learning methods, proposing new features for acceleration, and studying their benefits, with a focus on LLM workloads and core deep learning kernels. | Serve | 9 |
| Senior Deep Learning Performance Architect Senior Deep Learning Performance Architect role at NVIDIA focused on developing and analyzing next-generation architectures for AI and HPC applications. This involves performance modeling, simulation, and understanding the interplay of hardware and software for deep learning training and inference. | ServePost-train | 9 |
| Senior Research Engineer - Autonomous Vehicles Senior Research Engineer at NVIDIA focusing on AI for Autonomous Vehicles. The role involves developing large-scale training frameworks for multimodal foundation models, optimizing GPU utilization, implementing data loaders, building simulation infrastructure, integrating new architectures, developing sim-to-real pipelines, combining LLMs with policy learning, and applying RL for fine-tuning LLMs. Requires expertise in deep learning, reinforcement learning, generative modeling, distributed training systems, and GPU acceleration. | Post-trainAgent | 9 |
| Senior Robotics Research Scientist NVIDIA's Seattle Robotics Lab is seeking a Senior Robotics Research Scientist to develop algorithms, models, and methods for robotic manipulation and loco-manipulation, integrating them into real-world systems and transferring research into NVIDIA products. The role involves fundamental and applied research across the robotics stack, with a focus on enabling companies to become robotics companies. | ShipData | 9 |
| Senior Research Engineer, Foundation Model Training Infrastructure Senior/Principal Engineer to build cutting-edge infrastructure for large-scale foundation model training in the Generalist Embodied Agent Research (GEAR) group, focusing on Project GR00T for humanoid robots. Responsibilities include designing and optimizing distributed training systems, data loaders, and monitoring tools for multimodal foundation models. | PretrainPost-train | 9 |
| Senior Manager, AlpaSim and AlpaDreams Production Engineering leader to scale NVIDIA's interactive world-model platform (OmniDreams, FlashDreams, AlpaSim) into an industry standard, focusing on production engineering, performance, and developer ecosystem growth for applications in AV, robotics, rendering, and simulation. | ShipServe | 8 |
| Senior Systems Software Engineer, Semiconductor Systems Inspection Senior Software Engineer to develop AI products for semiconductor inspection, focusing on computer vision, multimodal AI, anomaly detection, model compression, and deployment optimization. The role involves building models, adaptation workflows, and inference pipelines for production environments, with a focus on advancing roadmap progress and delivering practical systems. | ShipServe | 8 |
| Senior Inference Engineer, AIConfigurator for Dynamo Senior Inference Engineer role focused on optimizing LLM inference deployment configurations using AIConfigurator, integrating GPU systems, model serving, and performance modeling for NVIDIA platforms. | Serve | 8 |
| Distinguished Engineer - Wireless Infrastructure NVIDIA is seeking a Distinguished Engineer to lead the technology strategy for next-generation wireless infrastructure, focusing on AI-RAN and Agentic Core. The role involves applying AI/ML to 6G RAN functions, transforming the wireless core into an agentic AI-based architecture, and driving rapid prototyping of GPU-accelerated platforms. Responsibilities include system architecture, design, development, and performance optimization for AI-for-RAN software stacks, as well as driving new applications in Integrated Sensing and Communications (ISAC) and Physical AI at the Edge. The position requires deep expertise in AI/ML, communication systems, and significant industry experience. | AgentData | 8 |
| Senior Software Engineer - Autonomous Driving Simulation Senior Software Engineer role focused on building and scaling realistic virtual environments for autonomous vehicle (AV) training, testing, and validation. The role involves developing simulation platforms, domain adaptation technologies (Real2Sim, Sim2Real), and optimizing large-scale simulation workflows. It requires strong programming skills in Python, C/C++, PyTorch, and experience with modern software engineering and infrastructure tools, as well as a background in computer vision, deep learning, or simulation systems. | DataAgent | 8 |
| Senior Applied AI Engineer, Product Simulation Senior Applied AI Engineer at NVIDIA to lead the rebuild of a silicon productization toolchain around AI. The role involves building agentic systems to demystify chip feature interactions, integrating AI tools into an agent harness, and leading eval-driven development for applied AI in production. | Agent | 8 |
| Senior Software Engineer, Agentic Engineering Senior Software Engineer to build agentic workflows for code generation, testing, and tuning within NVIDIA's frameworks and compilers. The role involves partnering with internal teams to develop and integrate AI agents into engineering processes, focusing on multi-agent orchestration and autonomous loops. | Agent | 8 |
| Systems Performance Engineer, Agentic AI Workloads – New College Grad 2026 This role focuses on modeling, simulating, and analyzing the system-level performance of agentic AI workloads in datacenter environments. The engineer will develop simulators, characterize LLM serving traffic, identify performance bottlenecks, and provide architectural recommendations for next-generation AI systems. The role requires strong programming skills in C++ and Python, a solid understanding of queueing theory, traffic modeling, and statistics, as well as fundamentals of deep learning and LLM inference serving. | ServeAgent | 8 |
| Software Engineering Manager, Robotics Neural Reconstruction and Real2Sim Applications NVIDIA is seeking an Engineering Manager to lead a team focused on robotics Neural Reconstruction & Real2Sim Applications, advancing technologies for creating digital twins and workflows at scale for physical AI. | ShipData | 8 |
| Senior Applied AI and AI Infrastructure Engineer - Chip Design and DFX Senior Engineer focused on Applied AI and AI Infrastructure for Chip Design and DFX at NVIDIA. The role involves building and managing deployment cycles for ML & Gen AI projects, establishing robust AI infrastructure, and applying AI methods to solve complex problems in Design For Test. Requires expertise in agents, multi-agentic ecosystems, SQL, ETL, data modeling, cloud platforms, and strong programming skills in Python/C++. | AgentServe | 8 |
| Applied AI Engineer - VLSI Design NVIDIA is seeking an Applied AI Engineer to develop and deploy AI agents leveraging LLMs to solve complex problems in VLSI design. The role involves designing and building infrastructure for LLM-powered engineering assistants and multi-turn dialogue systems, fine-tuning models, and integrating them with CAD flows. | Agent | 8 |
| Senior ASIC AI Engineer Develop AI powered methodologies and Agents to generate micro-architecture, RTL, and physical design starting with specification, using AI agents to process large data and existing codebase to generate skills that can be widely used. Evaluate latest Multi-agent collaboration frameworks and apply them to generate area/power/timing/functionally accurate designs for memory system units in the GPU. | Agent | 8 |
| Deep Learning Computer Architect - New College Grad 2026 NVIDIA is seeking a Deep Learning Computer Architect to design hardware accelerator and processor architectures for next-generation platforms, enabling state-of-the-art machine learning and data analytics. The role involves analyzing DL methods, proposing new features for acceleration, and studying their benefits, with a focus on LLM workloads and deep learning kernels. | Serve | 8 |
| Senior Manager, Artificial Intelligence - Machine Learning Platform Senior Manager for AI/ML Platform at NVIDIA, leading the development and management of tools and services for the entire AI/ML project lifecycle, focusing on large-scale model training and deployment efficiency. Requires extensive experience in AI/ML infrastructure, team leadership, and strategic vision for AI platforms. | ServePost-train | 8 |