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. Our 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 an amazing and collaborative research team that consistently produces influential works on multimodal foundation models, large-scale robot learning, game AI, and physical simulation. Our past projects include Eureka, VIMA, Voyager, MineDojo, MimicPlay, Prismer, and more. One of our team’s most recent milestones includes Project GR00T, a foundation model for humanoid robots. Your contributions will have a significant impact on our moonshot research projects and product roadmaps.
What you'll be doing:
- 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 all of NVIDIA to transfer research to products and services.
What we need to see:
- 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 the following topics: 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, such as reinforcement learning, imitation learning, classical control methods, etc.
- 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.
NVIDIA is widely considered to be one of the technology world's most desirable employers. We have some of the most forward-thinking and productive people in the world. Please join us and be part of the forefront of developing general-purpose robots and embodied agents!
