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 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).
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.
| Title | Stage | AI score |
|---|---|---|
| Senior Applied Deep Learning Scientist - Large Vision Language Models NVIDIA is seeking a Senior Applied Deep Learning Scientist to work on multimodal language models, specifically the Nemotron Omni family. The role involves pushing the boundaries of these models for downstream applications, preparing large-scale multimodal datasets, and collaborating globally to turn research into impactful products. The position spans the full pipeline from pre-training to post-training, with a focus on open models, weights, and data for real-world applications. | Post-trainData | 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. |
| 9 |
| Senior Deep Learning Software Engineer, Inference Senior Software Engineer specializing in Deep Learning Inference, focusing on optimizing GPU-accelerated software for large-scale model serving and inference using frameworks like SGLang and vLLM. The role involves performance tuning, implementing latest algorithms, and scaling performance across NVIDIA accelerators. | Serve | 9 |
| Solutions Architect - AI for Drug Discovery 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. | ServePost-train | 8 |
| Principal AI Developer Technology Engineer 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. | Serve | 8 |
| Solution Architect, Financial Services 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. | Post-trainPretrain | 8 |
| Senior Deep Learning Compiler Engineer - PyTorch Senior Deep Learning Compiler Engineer to develop and optimize PyTorch models for NVIDIA GPUs using compiler technology like Thunder, TorchDynamo, and TorchInductor. Focus on performance analysis and contributing to open-source AI ecosystem. | Serve | 8 |
| 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 |
| Solution Architect, Financial Services 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. | Serve | 7 |