PhD Research Intern, Generative AI for Physical AI - 2027

NVIDIANVIDIASanta Clara, California, United States
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Posted

9/15/2026

Employment

Intern

Range

$38 - $94/hr

Work style

On-site

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AI summary

Core responsibilities

Conduct research in generative AI, multimodal foundation models, and embodied AI to advance Physical AI. Develop algorithms for video understanding, simulation, and policy learning while collaborating with cross-functional teams.

Requirements overview

Currently pursuing a PhD in CS, EE, Robotics, or related fields. Requires strong Python and PyTorch skills with a background in generative AI, computer vision, or reinforcement learning.

Key skills

Generative AIMultimodal foundation modelsWorld modelsEmbodied AIComputer visionReinforcement learningPythonPyTorchRoboticsAutonomous drivingVideo understandingPolicy learningDistributed trainingSimulationMachine learning

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Education requirements

postgraduate degree

About NVIDIA

Industry

Computer Hardware Manufacturing

Employees

52,027

Type

Public Company

Size

10,001+ employees

Since its founding in 1993, NVIDIA (NASDAQ: NVDA) has been a pioneer in accelerated computing. The company’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined computer graphics, ignited the era of modern AI and is fueling the creation of the metaverse. NVIDIA is now a full-stack computing company with data-center-scale offerings that are reshaping industry.

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Job categories

TechnologyScience & ResearchSoftwareEngineeringData & Analytics

Description

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.

Requirements

  • Generative AI
  • Multimodal foundation models
  • World models
  • Embodied AI
  • Computer vision
  • Reinforcement learning
  • Python
  • PyTorch
  • Robotics
  • Autonomous driving
  • Video understanding
  • Policy learning
  • Distributed training
  • Simulation
  • Machine learning

Benefits

  • Intern benefits

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