Research Scientist, Generalist Embodied Agent Research - Phd New College Grad 2026

Details

NVIDIA is searching for an outstanding research scientist to build humanoid robot foundation models and systems in the Generalist Embodied Agent Research (GEAR) group. Everything that moves will eventually be autonomous. Their mission is to build general-purpose embodied agents that learn to explore and master complex skills across the virtual and the physical world.

You will work with a collaborative research team that produces influential works on multimodal foundation models, large-scale robot learning, game AI, and physical simulation. Past projects include Eureka, VIMA, Voyager, MineDojo, MimicPlay, Prismer, and Project GR00T (a foundation model for humanoid robots). Your contributions will impact moonshot research projects and product roadmaps.

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 across NVIDIA to transfer research to products and services

Requirements

• Ph.D. in Computer Science/Engineering, Electrical Engineering, etc., or equivalent research experience
• Outstanding engineering skills in rapid prototyping and model training frameworks (PyTorch, Jax, Tensorflow, etc.); Python or C++ is required; CUDA or ROS proficiencies are a plus
• Excellent knowledge and hands-on experience for training LLMs, multimodal foundation models, or large generative models
• Experience in foundation and diffusion models, reinforcement learning, agent learning, and applied robotics
• Experience across one or both of these fields:
  • Multimodal Foundation Models
    • Hands-on training experience and publications in at least one of: LLMs; large vision-language models; video generative models and diffusion algorithms; action-based transformers
    • Excellent skills in working with large-scale machine learning/AI systems and compute infrastructure
  • Robotics
    • Hands-on training experience and publications in robot learning (e.g., 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 including PID, model predictive control, and whole-body control
    • Familiarity with physics simulation frameworks such as MuJoCo and Isaac Sim
    • Robot hardware design and hands-on building experience

Benefits

• Eligible for equity and benefits (as described on NVIDIA’s benefits page)