Research Scientist, Generative AI for Physical AI - PhD New College Grad 2026
at Nvidia
USD 168,000-264,500 per year
Used Tools & Technologies
GPU GenAIRequired Skills & Competences
Tag name is followed by "@" symbol and proficiency level value.
About proficiency levels:
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
Algorithms @ 3
PyTorch @ 3
Generative AI @ 3
AI @ 3
Reinforcement Learning @ 3
Robotics @ 3
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
Details
Are you passionate about pushing the boundaries of AI at the intersection of the digital and physical worlds? Join our groundbreaking research team as we revolutionize the future of physical AI through generative models. You will work with state-of-the-art technology and have access to massive computational resources.
Responsibilities
- Pioneer generative AI algorithms for physical AI applications, focusing on advanced video generative models and video-language models
- Architect and implement data processing pipelines to produce high-quality training data for Generative AI and Physical AI systems
- Design and develop physics simulation algorithms to enhance Physical AI training
- Scale and optimize large-scale training systems to efficiently harness 20,000+ GPUs for training foundation models
- Author research papers to share discoveries with the global AI community
- Collaborate with research teams, internal product groups, and external researchers
- Facilitate technology transfer and contribute to open-source initiatives
Requirements
- PhD in Computer Science, Computer Engineering, Electrical Engineering, or a related field (or equivalent experience)
- Deep expertise in PyTorch and related libraries for Generative AI and Physical AI development
- Strong foundation in diffusion models, vision-language models, and reasoning models and their applications
- Proven experience with reinforcement learning algorithms and implementations
- Robust knowledge of physics simulation and its integration with AI systems
- Demonstrated proficiency in 3D generative models and their applications
- Experience or ability to work with large-scale distributed training systems
Ways to Stand Out
- Publications or contributions to major AI conferences (ICLR, NeurIPS, ICML, CVPR, ECCV, SIGGRAPH, ICCV, etc.)
- Experience with large-scale distributed training systems
- Background in robotics or physical systems
- Open-source contributions to prominent AI projects
- History of successful research-to-product transitions
Compensation & Benefits
- Base salary range: 168,000 USD - 264,500 USD
- Eligible for equity and company benefits
Additional Information
- Applications accepted until April 14, 2026
- NVIDIA uses AI tools in its recruiting processes
- NVIDIA is an equal opportunity employer and is committed to fostering a diverse work environment.