Reinforcement Learning Engineer - Whole Body Control

Job Description

Develop and implement reinforcement learning algorithms for locomotion and loco-manipulation tasks. Design and optimize simulation environments for policy training and conduct sim-to-real transfer.

Requirements: Candidates should have an M.S. or Ph.D. in a relevant field and solid experience with reinforcement learning algorithms and simulation platforms. Proficiency in Python and/or C++ and familiarity with machine learning frameworks is also required.

Key Skills: Reinforcement Learning, Simulation Platforms, Policy Optimization, Python, C++, Machine Learning, Sensor Fusion, Feedback Control, Proprioceptive Sensing, Analytical Skills, Debugging Skills, Robotics, Locomotion, Motion Control, System Identification, Domain Randomization