NVIDIA
- HQ
- California, US
- Founded
- 1993
- Size
- 35,000+
- Website
- nvidia.com
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).
Currently tracking 440 active AI roles, down 53% versus the prior 4 weeks. Primary focus: Serve · Engineering. Salary range $100k–$575k (avg $262k).
| Title | Stage | AI score |
|---|---|---|
| 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, 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 |
| 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 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 |
| 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 |
| 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 Software Engineer, RL Post-Training Frameworks 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. | Post-trainServe | 9 |
| Senior Machine Learning and Simulation Engineer - Autonomous Vehicles 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. | Post-trainAgent | 9 |
| Deep Learning Senior Engineer, End-To-End Autonomous Driving 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. | Post-trainAgent | 9 |
| Principal Deep Learning Senior Engineer, End-To-End Autonomous Driving 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. | Post-trainAgent | 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 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 |
| 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 |
| 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 |
| 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 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 Scientific Machine Learning Engineer – Earth-2 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. | Post-train | 8 |
| Research Scientist, Security and Privacy - PhD New College Grad 2026 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. | Post-train | 8 |
| Senior Research Scientist, Security and Privacy NVIDIA is seeking security and privacy researchers to develop secure, private, and safe AI systems. The role involves understanding vulnerabilities, developing hardware/software/algorithms for trustworthy AI, collaborating across teams, and publishing research. Requires a Ph.D. in a relevant field, expertise in security areas, and coding skills. | Post-train | 7 |