PhD Research Intern, Physical AI - Foundation Models

Nvidia

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Work type
On-site
Location
Santa Clara, CA
Employment
Full-time
Posted
9 days ago
Freshness
Confirmed live yesterday
Nearby
99+ roles within 25 mi

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Similar $218k
$155k most similar roles pay here $291k

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About Nvidia

Nvidia is a leading designer of graphics processing units (GPUs) and system-on-chip units, powering gaming, professional visualization, data centers, and artificial intelligence workloads. Industry: Semiconductors & AI Computing

Nvidia currently has 1150 open roles on FindRole.

Listed pay typically runs $184,000–$287,500 across 912 roles with salary data.

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TL;DR · PhD Research Intern, Physical AI - Foundation Models

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As a PhD Research Intern, Physical AI - Foundation Models - 2027, you will join the team building Cosmos world foundation models and generative AI systems for robotics, autonomous driving, smart spaces, and embodied agents. You will conduct research in generative AI, multimodal foundation models, world models, and embodied AI while developing algorithms for video understanding, action-conditioned simulation, multimodal reasoning, and policy learning. Your daily work involves training and evaluating large-scale models using video, image, language, and robotics or autonomous driving data to solve problems in multimodal world understanding and synthetic data generation. You will utilize Python and PyTorch to advance the frontier of Physical AI. The role requires expertise in computer vision, reinforcement learning, and distributed training while collaborating across research teams to publish at top conferences and integrate innovations into products.

Skills

Generative AI Multimodal Foundation Models World Models Python PyTorch Computer Vision Reinforcement Learning Distributed Training Robotics Autonomous Driving Video Understanding Simulation VLMs Policy Learning

What you'll do

  • Conduct research in generative AI, multimodal foundation models, world models, and embodied AI.
  • Develop algorithms for video understanding, generation, action-conditioned simulation, and multimodal reasoning.
  • Develop methods for policy learning in robotics and autonomous driving contexts.
  • Train and evaluate large-scale models using video, image, language, and robotics data.
  • Publish original research findings at top-tier academic conferences.
  • Translate innovative research findings into functional NVIDIA products.

What we're looking for

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

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