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 |
|---|---|---|
| Principal High-Performance LLM Training Engineer NVIDIA is seeking a Principal Engineer to lead performance analysis and optimization of large-scale AI training and post-training workloads on NVIDIA's hardware and software stack. The role involves deep technical analysis across compute, memory, communication, and frameworks to improve efficiency and influence future roadmaps. | PretrainPost-train | 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 |
| Solutions Architect, Pre-training and Post-training NVIDIA is seeking a Solutions Architect to assist researchers and developers in accelerating their AI workloads using NVIDIA's platform. The role involves creating technical engagements, proposing state-of-the-art training and optimization frameworks, and promoting collaborative results. Requires 5+ years of experience in the full AI model lifecycle, including pre-training, fine-tuning, post-training, optimization, and evaluation, along with strong software engineering skills. | PretrainPost-train | 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 LLM Train Framework Engineer NVIDIA is seeking a Senior LLM Train Framework Engineer to contribute to the Megatron Core team, focusing on building and developing open-source frameworks for LLM and Multimodal foundation model pretraining and post-training. The role involves addressing AI training and inference challenges across the model lifecycle, enhancing distributed training strategies, and optimizing performance on NVIDIA GPUs. | PretrainPost-train | 9 |