Research Scientist: Physical AI & Foundation Models

NVIDIA Corporation; Santa Clara (CA); Hybrid; USD 168,000 - 265,000; Full time

Benefits offered by this job

Equity

Job summary

NVIDIA Corporation in Santa Clara, CA is seeking a Research Scientist for Physical AI—Foundation Models. You will pioneer generative AI algorithms, design physics-based training pipelines, and scale training across 20,000+ GPUs to advance physical AI research.

PhD required with deep PyTorch expertise and a strong background in diffusion, vision-language, and RL. Collaboration across teams and open-source contributions are encouraged, with equity and competitive compensation.

Qualifications

• PhD in Computer Science, Computer Engineering, Electrical Engineering, or related field.
• Deep expertise in PyTorch and related libraries for Generative AI and Physical AI.
• Strong foundation in diffusion, vision-language and reasoning models.
• Proven experience with reinforcement learning implementations.
• Robust knowledge of physics simulation and AI integration.
• Demonstrated proficiency in 3D generative models and applications.

Responsibilities

• Pioneer revolutionary generative AI algorithms for physical AI applications.
• Architect data pipelines to produce high-quality training data.
• Design physics simulation algorithms to enhance Physical AI training.
• Scale and optimize large-scale training systems for 20,000+ GPUs.
• Publish influential research papers and collaborate with teams.
• Contribute to open-source projects and transfer technology to products.

Skills

PyTorch

Diffusion models

Video-language models

Reinforcement learning

3D generative models

Physics-aware AI

Large-scale training

Education

PhD in Computer Science/Engineering or related field

Tools

PyTorch

Job description

NVIDIA Corporation in Santa Clara, CA is seeking a Research Scientist for Physical AI—Foundation Models. You will pioneer generative AI algorithms, design physics-based training pipelines, and scale training across 20,000+ GPUs to advance physical AI research.

PhD required with deep PyTorch expertise and a strong background in diffusion, vision-language, and RL. Collaboration across teams and open-source contributions are encouraged, with equity and competitive compensation.