Reinforcement Learning Researcher (Humanoid)

REK
San Francisco, CA
Category Engineering
Job Description
We are seeking a Humanoid Robot Reinforcement Learning Researcher to develop and train advanced control policies for our REK humanoid robots. The researcher will work closely with REK's robotics, simulation, and teleoperation teams to design reinforcement learning pipelines that improve movement quality, stability, responsiveness, and adaptability all optimized for real-time fighting performance.

Requirements

  • 2+ years of hands-on experience in reinforcement learning for humanoid robots
  • Deep understanding of deep RL algorithms
  • Experience using Isaac Gym, MuJoCo, PyBullet, or Gazebo for simulation training
  • Strong software engineering skills in Python, PyTorch, and C++
  • Understanding of robot kinematics, dynamics, and control systems

Benefits

  • Competitive salary based on experience
  • Equity participation in a rapidly growing robotics entertainment startup
  • Full benefits
  • Access to REK's humanoid robotics lab and training infrastructure
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