Reinforcement Learning Engineer

Figure is an AI Robotics company developing a general purpose humanoid. Our Humanoid is designed for corporate tasks targeting labor shortages and jobs that are undesirable or unsafe. We are based in Sunnyvale, CA and require 5 days/week in-office collaboration. It's time to build. We are looking for a Reinforcement Learning Engineer. You will own the development, training, and deployment of new reinforcement learning algorithms for our humanoid robot as well as building infrastructure to support training policies at a large scale. Responsibilities: Develop, train, and deploy reinforcement learning algorithms for locomotion and manipulation tasks Build simulation infrastructure to support the training of locomotion and manipulation policies for a general purpose humanoid robot at a large scale Collaborate with the controls team to integrate policies into the existing control stack Define, test, and evaluate performance metrics for learned policies Requirements: Confident writing production quality code in PyTorch Familiar with online and offline reinforcement learning algorithms: 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. Familiarity with general ML evaluation tools such as TensorBoard, Weights&Biases, etc. Bonus Qualifications: Experience transferring policies learned in simulation to robot hardware Experience training locomotion policies for quadrupedal or bipedal robots