Reinforcement Learning Engineer – Whole Body Control
Core
Develop, train, deploy, and evaluate reinforcement learning algorithms for whole body control of autonomous humanoid robots.
Role type
Senior IC reinforcement learning engineer (robotics)
Builds
Whole-body control policies for humanoid robots
Domain
Robotics / AI
Deliverable
production ML models
Required skills
dynamics and control, legged robots, reinforcement learning algorithms (PPO, SAC), hyperparameter tuning, cost function design, domain randomization, curriculum learning, reward shaping
Preferred skills
behavior cloning, model distillation
Technologies
PPO, SAC
Responsibilities
Develop, train, and deploy RL algorithms for whole body control; Determine observations, actions, and model types for maximum performance; Identify and close sim-to-real gaps; Define, test, and evaluate performance metrics for learned policies; Harden the control stack for robustness; Lead complex controls projects and mentor junior engineers
Seniority
Senior, hands-on IC with mentorship
