Research Scientist, Reinforcement Learning - Atlas
Core
Design, train, and deploy reinforcement learning (RL) policies for whole-body mobile manipulation and dexterous manipulation on humanoid robots in unstructured environments.
Role type
Research Scientist (Reinforcement Learning & Robotics)
Builds
RL policies for Atlas humanoid robots
Domain
Robotics, Reinforcement Learning, Whole-body Control
Deliverable
production ML models
Required skills
Reinforcement Learning, Robotics (kinematics, dynamics), Python, C++, Simulation (Isaac Sim, MuJoCo), ML frameworks (PyTorch, TensorFlow, RLlib), Algorithm design, Performance optimization
Preferred skills
Physical robot deployment, Locomotion, Bimanual manipulation, Open-source contributions, Top-tier conference publications
Technologies
Isaac Sim, MuJoCo, PyTorch, TensorFlow, RLlib, Python, C++
