Senior Research Scientist, Multimodal Foundation Models and Robotics

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.

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 ↗ (external site), VIMA ↗ (external site), Voyager ↗ (external site), MineDojo, MimicPlay ↗ (external site), Prismer ↗ (external site), and more. One of our team’s most recent milestones includes Project GR00T ↗ (external site), a foundation model for humanoid robots. Your contributions will have a significant impact on our moonshot research projects and product roadmaps.

What you will 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:

• 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
• 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.
• Robotics:
• 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.

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!

Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 192,000 USD - 304,750 USD for Level 4, and 224,000 USD - 356,500 USD for Level 5.

You will also be eligible for equity and benefits ↗ (external site).

Applications for this job will be accepted at least until May 5, 2026.

This posting is for an existing vacancy.

NVIDIA uses AI tools in its recruiting processes.

NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.