
Reinforcement Learning Engineer – Whole Body Control at Figure AI
San Jose, CAFull-timeControlsPosted 6 months ago
Apply with PipelineAbout the Role
<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 $150,000 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>
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