Reinforcement Learning Engineer, Whole Body Control

Job summary

Responsibilities

We are looking for a Reinforcement Learning Engineer to develop, train, deploy, and evaluate advanced reinforcement learning algorithms for whole body control of our humanoid robot.

• Develop, train, and deploy reinforcement learning algorithms for whole body control.
• Determine the observations, actions, and model types that unlock maximum performance.
• Identify and close the most important sim-to-real gaps.
• Define, test, and evaluate performance metrics for learned policies.
• Harden the control stack to ensure rock solid robustness.

What they're looking for

• Strong background in dynamics and control, ideally of legged robots.
• Experience with reinforcement learning algorithms for robotics: PPO, SAC, etc.
• Experience tuning hyperparameters and cost functions for these RL algorithms.
• Familiarity with common RL techniques such as: domain randomization, curriculum learning, reward shaping, etc.
• Capable of leading complex controls projects and mentoring junior engineers.