Helix Ai Engineer, Reinforcement Learning

Figure

San Jose, CA, United States
On-site
Reinforcement learning algorithms
Embodied agents
Python and pytorch
Figure is developing autonomous general-purpose humanoid robots with a goal to build embodied AI systems that can perceive, reason, and act in the real world

Job Summary

  • Figure is developing autonomous general-purpose humanoid robots with a goal to build embodied AI systems that can perceive, reason, and act in the real world.
  • The Helix team is responsible for developing core AI systems for humanoid autonomy, focusing on reinforcement learning for skill acquisition.
  • This role requires 5 days/week in-office collaboration in San Jose, CA, and involves designing and implementing RL algorithms for embodied agents in real-world and simulated environments.

Matching Summary

Figure is developing autonomous general-purpose humanoid robots with a goal to build embodied AI systems that can perceive, reason, and act in the real world.

Skills & Requirements

Must-have

  • Reinforcement learning algorithms
  • Embodied agents
  • Python and PyTorch
  • Large-scale experimentation
  • Distributed training systems
  • Solid software engineering skills

Nice-to-have

  • RL to robotics
  • Large-scale RL infrastructure
  • Offline RL, imitation learning
  • Reward modeling, human-in-the-loop
  • Leading AI labs experience
  • Robotics systems, simulation environments

Key Requirements

  • Experience developing and applying RL algorithms
  • Strong understanding of RL fundamentals
  • Experience training policies in simulation/real-world
  • Proficiency in Python and PyTorch
  • Experience with large-scale experimentation
  • Strong experimental rigor
  • Solid software engineering skills
  • Ability to operate independently

Work Rights

Not specified

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