About the job
We are now looking for a Senior Research Scientist focused on Multimodal Foundation Models and Robotics! 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.
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 all of NVIDIA to transfer research to products and services.
Qualifications
Minimum
A Ph.D. in Computer Science/Engineering, Electrical Engineering, etc., or equivalent research experience.
5 years of relevant work/research experience across one or both of these fields: Multimodal Foundation Models; Robotics
Preferred
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; or Action-based transformers.
Outstanding engineering skills in rapid prototyping and model training frameworks (PyTorch, Jax, Tensorflow, etc.). Python is required; C++ and CUDA proficiencies are a big plus;
Excellent skills in working with large-scale machine learning/AI systems and compute infrastructure.
Hands-on training experience and publications in robot learning, such as reinforcement learning, imitation learning, classical control methods, etc.
Strong programming skills in Python, C++, ROS, and machine learning frameworks like PyTorch.
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.