Staff Reinforcement Learning Engineer – Whole Body Control

Job description

Figure is an AI Robotics company autonomous general-purpose humanoid robots. The goal of the company is to ship humanoid robots with human level intelligence. Its robots are engineered to perform a variety of tasks in the home and commercial markets. We are based in North San Jose, CA and require 5 days/week in-office collaboration. It’s time to build. We are looking for a Staff Reinforcement Learning Engineer to develop, train, deploy, and evaluate advanced reinforcement learning algorithms for whole body control of our humanoid robot. Requirements: - 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 - 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...