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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

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