Research Scientist, Physical AI - Foundation Models - PhD New College Grad 2026
Immigration summary
Visa sponsorship
This employer sponsors this kind of work repeatedly, and is still filing this year.
2,042 recent H-1B filings · 97 similar-role filings
View visa evidenceGreen card sponsorship
This employer has recently sponsored green cards at scale.
443 recent certified PERM filings · 8 similar-role filings
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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 groundbreaking generative models. We are now hiring Research Scientists to join our Cosmos team!
As a Research Scientist specializing in Generative AI for Physical AI, you'll be at the forefront of developing next-generation algorithms that bridge the gap between virtual and physical realms. You'll work with state-of-the-art technology and have access to massive computational resources to bring your ideas to life.
What you'll be doing:
Pioneer revolutionary generative AI algorithms for physical AI applications, with a focus on advanced video generative models and video-language models
Architect and implement sophisticated data processing pipelines that produce premium-quality training data for Generative AI and Physical AI systems
Design and develop cutting-edge physics simulation algorithms that enhance Physical AI training
Scale and optimize large-scale training systems to efficiently harness the power of 20,000+ GPUs for training foundation models
Author influential research papers to share your groundbreaking discoveries with the global AI community
Drive innovation through close collaboration with research teams, diverse internal product groups, and external researchers
Build lasting impact by facilitating technology transfer and contributing to open-source initiatives
What we need to see:
PhD in Computer Science, Computer Engineering, Electrical Engineering, or related field (or equivalent experience).
Deep expertise in PyTorch and related libraries for Generative AI and Physical AI development
Strong foundation in diffusion, vision language 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
Ways to stand out from the crowd:
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
You'll be part of a team that's defining the future of Physical AI, with access to world-class computing resources and the opportunity to work on problems that matter. Your research won't just live in papers – it will be implemented in real-world systems that push the boundaries of what's possible in AI. Join us in shaping the future of AI where digital intelligence meets physical reality. NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most forward-thinking and hardworking people in the world working for us. Are you a creative and autonomous research scientist with a genuine passion for advancing the state of AI? If so, we want to hear from you!
Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 168,000 USD - 264,500 USD.
You will also be eligible for equity and benefits.
Applications for this job will be accepted at least until September 27, 2026.
This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.
NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.
Sponsorship evidence
Why Openbound reached the conclusions above.
Visa sponsorship evidence
Current posting
Silent on sponsorship
Employer H-1B history
- 2,042
- recent certified H-1B filings
- 1,364
- new-hire petitions
- 97
- filings for similar roles
- 2,424
- so far in FY2026
Filed titles like this role: research scientist
More evidence details
- 97 certified H-1B filings for this same role, 1,364 new-hire petitions across the employer, and 1,304 new hires already this year
- 97 certified H-1B filings for this same role
- 2,042 recent certified H-1B filings across the employer
- Still filing this year — 2,424 filings in FY2026
- 554 USCIS H-1B new-employment approvals, counted separately from LCA filings
- Strong filing activity in CA
- 1,987 further USCIS approvals for extensions or transfers
- The posting says nothing about sponsorship either way
Strong filing activity in CA.
Green card sponsorship evidence
Employer PERM history
- 443
- recent certified PERM filings
- 8
- filings for similar roles
- 384
- filings in this location
Filing history reflects past employer behavior; it isn't a promise for this opening.
All open roles at NvidiaHow Openbound evaluates sponsorship
Visa history uses official U.S. Department of Labor H-1B LCA disclosure data and USCIS H-1B petition history. Green card history uses DOL PERM disclosure data. Each is read for the employer as a whole, for roles like this one, and for this location, weighted toward the most recent fiscal years.
An employer is matched to its filing entities by verified legal name and reviewed aliases; a match is never made on a name resemblance alone. Where no verified entity can be matched, the page says so and draws no conclusion from the absence. 467 filing titles were examined for this employer.
What this posting states outranks history in both directions, and an employer's published policy outranks past filings. Filing history reflects past behavior; it is not a promise of sponsorship for this opening, and none of this is legal advice.