NVIDIA
- HQ
- California, US
- Founded
- 1993
- Size
- 35,000+
- Website
- nvidia.com
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 |
|---|---|---|
| Applied AI Researcher - World Reconstruction and Generation NVIDIA is seeking an Applied AI Researcher to work on NuRec-related research in world reconstruction and generation, developing and adapting Deep Learning-based methods for tasks like novel view synthesis, generative modeling, and neural rendering. The role involves prototyping with Python/PyTorch, building evaluation and agentic AI-assisted research workflows, and turning research into usable technology. Requires a PhD or MS with significant experience in ML/DL, Computer Graphics, Computer Vision, or 3D reconstruction, with strong Python/PyTorch skills. | Post-trainAgent | 9 |
| Senior Software Engineer, AI Inference Systems 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. |
| Serve |
| 9 |
| Senior HPC and AI Network Software Architect 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. | ServePost-train | 9 |
| Senior Deep Learning Engineer 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. | ServePost-train | 9 |
| Senior GPU Networking Architect 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. | Serve | 9 |
| Senior Manager, Interactive World Model Platforms Engineering leader to scale NVIDIA's interactive world-model platform (OmniDreams, FlashDreams) into an industry standard, focusing on production engineering, performance, and developer/researcher success across AV, robotics, rendering, and simulation. | ShipServe | 8 |
| Senior Software Engineer, JAX 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. | Serve | 8 |
| Principal AI Developer Technology Engineer 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. | Serve | 8 |
| Senior Software Architect - Deep Learning and HPC Communications This role focuses on architecting and implementing next-generation communication software and platforms for deep learning and high-performance computing (HPC) applications, specifically targeting the efficient scaling of GPU clusters. The work involves identifying performance bottlenecks, designing new communication technologies, exploring hardware/software co-design, and using simulation to evaluate performance at massive scales. | Serve | 8 |
| Principal Simulation Engineer, Industrial Physics and Robotics NVIDIA is seeking a Principal Simulation Engineer to lead the development of advanced physically based simulation systems for robotics and industrial digital twins. This role requires deep expertise in multibody dynamics, contact, friction, and flexible bodies, with a focus on integrating simulation with robotics workflows and applying modern AI-assisted and agentic development. The ideal candidate has a track record of building production-level simulation software and experience validating simulators against physical systems. | Agent | 7 |
| Senior Quantum Algorithm Researcher NVIDIA is seeking a Senior Quantum Algorithm Researcher to lead collaborations and research in AI for quantum algorithms, contributing to NVIDIA's quantum products and driving innovation at the intersection of quantum computing and AI. The role involves establishing partnerships, publishing research, and supporting customer adoption. | Pretrain | 7 |
| Senior HPC AI Cluster Engineer NVIDIA is seeking an experienced HPC-AI Engineer to join their Networking Clusters Solutions Infrastructure team. The role involves designing, implementing, and maintaining large-scale HPC/AI clusters, managing job schedulers, developing CI/CD pipelines, and automating infrastructure deployment and monitoring. The engineer will work with cutting-edge hardware and software, support R&D, and engage in POCs for future improvements. | Serve | 7 |
| Senior Machine Learning Applications and Compiler Engineer, LPX 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. | Serve | 7 |
| Senior Networking Solution Test Engineer – AI Cluster Debugging 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. | Serve | 7 |