NVIDIAPosted 1w ago

PhD Research Intern, Physical AI - Foundation Models - 2027

PhD Research Intern, Physical AI - Foundation Models - 2027 at NVIDIA scores 95 out of 100 on AI centrality, which makes it AI Level 4 of 4 (Builds AI) on this board. The level measures how much of the work is AI, not seniority.

US, CA, Santa ClarainternFull time$38-$94/hr

AI in this role

Conduct PhD-level research in generative AI, multimodal foundation models, and embodied AI as a research intern at NVIDIA.

pytorchpython

computer-visiongenerative-aimultimodal-learningroboticsreinforcement-learning

At NVIDIA, we are building Cosmos world foundation models and generative AI systems for Physical AI across robotics, autonomous driving, smart spaces, and embodied agents.

The NVIDIA Cosmos Platform enables multimodal world understanding, simulation, synthetic data generation, and embodied reasoning. We are looking for outstanding PhD interns to help advance the frontier of Physical AI and world models.

What you’ll be doing:

Conduct research in generative AI, multimodal foundation models, world models, and embodied AI.
Develop algorithms for video understanding/generation, action-conditioned simulation, multimodal reasoning, and policy learning.
Train and evaluate large-scale models using video, image, language, and robotics or autonomous driving data.
Collaborate with researchers and engineers across AI, robotics, simulation, and graphics teams.
Publish research at top conferences and transfer innovations into NVIDIA products.

What we need to see:

Currently pursuing a PhD in CS, EE, Robotics, or related fields.
Strong background in generative AI, computer vision, multimodal learning, robotics, or reinforcement learning.
Prior publication record and research experience.
Strong Python and PyTorch skills.

Ways to stand out from the crowd:

Experience with large-scale foundation model training.
Research in video models, VLMs, world models, robotics, or autonomous driving.
Experience with distributed training, simulation, or embodied AI.

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. If you're creative and autonomous, we want to hear from you!

Our internship hourly rates are a standard pay based on the position, your location, year in school, degree, and experience. The hourly rate for our interns is 38 USD - 94 USD.


You will also be eligible for Intern benefits.

Applications for this job will be accepted at least until September 19, 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.

Prepare for this job

A free preview built only from this posting: what it asks for, what you could be asked in an interview, and how to adjust your resume.

Skills and AI tools this role asks for

Computer VisionGenerative AIMultimodal LearningRoboticsReinforcement LearningPyTorchPython

Questions you could be asked

Walk me through a computer vision problem you solved, from raw data to a deployed model.
Tell me about a project where generative ai was part of your work. What did you do?
Tell me about a project where multimodal learning was part of your work. What did you do?
Tell me about a project where robotics was part of your work. What did you do?
Tell me about a project where reinforcement learning was part of your work. What did you do?

Adapt your resume

List these exact terms on your resume: Computer Vision, Generative AI, Multimodal Learning, Robotics, and Reinforcement Learning. An applicant tracking system matches the wording, not the idea.
Attach one line of real, concrete experience to at least one of them — a tool named with nothing behind it rarely survives a human read.
Lead with what you built, trained or shipped — this role is judged on the AI system itself, not the tools around it.

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