PhD Research Intern, Generalist Embodied Agents Research - 2027
$0k - $0k • Remote • US, CA, Santa Clara
Posted 7d ago
Job Location
US, CA, Santa Clara
Tech Stack
Remote Work Policy
Fully remote
Categories
AI Research Engineer
About the job
NVIDIA is seeking a research intern to contribute to building humanoid robot foundation models and systems within the Generalist Embodied Agent Research (GEAR) group. The mission is to create general-purpose embodied agents capable of learning and mastering complex skills in both virtual and physical environments. You will collaborate with a research team known for influential work in multimodal foundation models, large-scale robot learning, game AI, and physical simulation, contributing to significant research projects and product roadmaps, including recent milestones like Project GR00T.
Responsibilities
- Design and implement novel AI algorithms and models for general-purpose humanoid robots and embodied agents.
- Develop large-scale AI training and inference methods for foundation models.
- Optimize and deploy AI models in physical simulation and on robot hardware.
- Collaborate with research and engineering teams to transfer research to products and services.
Requirements
- Currently pursuing a PhD degree in Computer Science/Engineering, Electrical Engineering, or a related field.
- Strong engineering skills in rapid prototyping and model training frameworks (PyTorch, Jax, Tensorflow).
- Proficiency in Python is required; C++ and CUDA proficiencies are a plus.
- Experience with large-scale machine learning/AI systems and computer infrastructure.
- Hands-on training experience and publications in at least one of the following: multimodal foundation models (LLMs, vision-language models, video generative models, diffusion models, action-based transformers) or robotics (robot learning, reinforcement learning, imitation learning, classical control methods).
- Deep understanding of robot kinematics, dynamics, and sensors.
- Ability to safely operate robot hardware, lab equipment, and tools.
- Knowledge of control methods (PID, MPC, whole body control).
- Familiarity with physics simulation frameworks (Mujoco, Isaac suite).
Benefits
- Internship hourly rates based on position, location, year in school, degree, and experience.
- Eligibility for Intern benefits.