Senior Researcher, Robot Learning & Foundation Models

What you'll do

• Build and evaluate learned policies, VLA models, and world models for manipulation and control.
• Develop data, simulation, evaluation, and sim-to-real systems for robot learning.
• Take research from experiments to reliable capabilities deployed on real robotic systems.

What they ask for

• Deep technical expertise in robot learning, reinforcement learning, imitation learning, control, or deep learning.
• Significant experience in at least one of robot manipulation, VLA models, world models, or robotics foundation models.
• Experience training and evaluating large-scale models using PyTorch or JAX, and running experiments end to end.
• Hands-on experience with robotics simulation and/or real-world deployment.

Nice to have

• Experience with large-scale reinforcement learning, diffusion- or transformer-based policies, world models, or embodied AI.
• Research publications, open-source contributions, or other impactful work in robotics or machine learning.

Tools

PyTorch, JAX, Isaac Sim, Isaac Lab, MuJoCo, Gazebo, PyBullet

AI focus

Robot learning and foundation models for manipulation and control, including VLA models, world models, reinforcement and imitation learning, and sim-to-real transfer.