Research Scientist, Generative AI for Physical AI - PhD New College Grad 2026

at Nvidia

📍 Santa Clara, United States

USD 168,000-264,500 per year

JUNIOR

✅ On-site

Tech Stack
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.

AI @ 3 Algorithms @ 3 GPU GenAI Generative AI @ 3 PyTorch @ 3 Reinforcement Learning @ 3 Robotics @ 3

Details

Are you passionate about pushing the boundaries of AI at the intersection of the digital and physical worlds? Join the Cosmos team to develop generative models for Physical AI. You will work with state-of-the-art technology and massive computational resources to advance next-generation AI systems.

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 that 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 using more than 20,000 GPUs to train foundation models.
Author research papers and 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, 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.

Preferred Qualifications

Publications or contributions to major AI conferences, including ICLR, NeurIPS, ICML, CVPR, ECCV, SIGGRAPH, and ICCV.
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 and Benefits

The base salary range is USD 168,000–264,500 per year. Compensation is determined based on location, experience, and the pay of employees in similar positions. The role also includes eligibility for equity and benefits.

Applications will be accepted at least until April 14, 2026. NVIDIA uses AI tools in its recruiting processes and is committed to fostering a diverse, equal-opportunity work environment.