Reinforcement Learning Engineer, Helix

Figure • San Jose, CA

39d • $150,000 - $400,000 • Onsite

About The Position

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 San Jose, 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.

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.

Nice To Haves

• Experience transferring policies learned in simulation to robot hardware
• Experience training locomotion policies for quadrupedal or bipedal robots

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

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: No Education Listed
• Number of Employees: 251-500 employees