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 |
|---|---|---|
| Deep Learning Senior Engineer, End-To-End Autonomous Driving NVIDIA is seeking a Deep Learning Senior Engineer to design, implement, and deploy end-to-end autonomous driving systems. The role focuses on AI 2.0, leveraging LLMs, VLMs, and VLAs for reasoning and planning in autonomous vehicles and robotics. Responsibilities include training large-scale models, building and fine-tuning LLM/VLM/VLA systems, exploring data generation strategies, and deploying models in production environments, integrating them with vehicle firmware. | Post-trainAgent | 9 |
| LLM Reinforcement Learning Framework Engineer NVIDIA is seeking an LLM Reinforcement Learning Framework Engineer to develop and deploy RL algorithms for LLM post-training, focusing on improving reasoning and alignment. The role involves integrating RL components into NVIDIA's LLM stack, crafting experiments, and ensuring production readiness. Requires strong Python, PyTorch, and practical RL experience with LLMs, along with familiarity in async/distributed orchestration. |
| Post-trainAgent |
| 9 |