Reinforcement Learning Engineer

Apptronik

Austin, TX, United States
On-site
State-of-the-art rl algorithms
Physical hardware deployment
Python for rapid prototyping
The Reinforcement Learning Engineer is a key, hands-on role focused on achieving state-of-the-art performance on our humanoid robots

Job Summary

  • The Reinforcement Learning Engineer is a key, hands-on role focused on achieving state-of-the-art performance on our humanoid robots.
  • You will join a team dedicated to bringing Apollo to market at scale, tackling the complex challenges like safety, commercialization, and mass production to change the world for the better.
  • As a senior member of the team, this individual will also be responsible for mentoring junior engineers, elevating the team's overall technical capabilities through their guidance and expertise.

Matching Summary

The Reinforcement Learning Engineer is a key, hands-on role focused on achieving state-of-the-art performance on our humanoid robots.

Skills & Requirements

Must-have

  • state-of-the-art RL algorithms
  • physical hardware deployment
  • Python for rapid prototyping
  • C++ for deployable code
  • robot dynamics and controls theory
  • human demonstration data pipelines

Nice-to-have

  • cutting edge embodied AI
  • human-centered robotics company
  • pushing the boundaries of robot capabilities
  • passion for seeing complex algorithms work

Key Requirements

  • 5+ years with common RL frameworks
  • 2+ years industry experience strongly preferred
  • PhD or MS in Computer Science, Robotics, or related field
  • Proven track record deploying learning-based policies on physical robots
  • Demonstrated experience mentoring engineers

Work Rights

Not specified

Tailored Resume

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