Figure is a Bay Area robotics startup building AI-powered humanoid robots for industrial tasks such as warehouse and factory work.
<p>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.</p> <p>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.</p> <p><strong>Key Responsibilities:</strong></p> <ul> <li>Develop, train, and deploy reinforcement learning algorithms for whole body control</li> <li>Determine the observations, actions, and model types that unlock maximum performance</li> <li>Identify and close the most important sim-to-real gaps</li> <li>Define, test, and evaluate performance metrics for learned policies</li> <li>Harden the control stack to ensure rock solid robustness</li> </ul> <p><strong>Requirements:</strong></p> <ul> <li>Strong background in dynamics and control, ideally of legged robots</li> <li>Experience with reinforcement learning algorithms for robotics: PPO, SAC, etc</li> <li>Experience tuning hyperparameters and cost functions for these RL algorithms</li> <li>Familiarity with common RL techniques such as: domain randomization, curriculum learning, reward shaping, etc.</li> <li>Capable of leading complex controls projects and mentoring junior engineers</li> </ul> <p><strong>Bonus Qualifications:</strong></p> <ul> <li>Experience with behavior cloning techniques (e.g. distillation)</li> </ul> <p>The US base salary range for this full-time position is between $200,000 and $350,000 annually.</p> <p>The pay offered for this position may vary based on several individual factors, including job-related knowledge, skills, and experience. The total compensation package may also include additional components/benefits depending on the specific role. This information will be shared if an employment offer is extended. </p>