Senior Reinforcement Learning Engineer

Apptronik

Austin, TX, United States
On-site
State-of-the-art rl algorithms
Physical hardware deployment
Python for rapid prototyping
Implement and deploy state-of-the-art RL algorithms to achieve ambitious, world-class performance on dynamic locomotion and manipulation tasks with physical hardware

Job Summary

  • Implement and deploy state-of-the-art RL algorithms to achieve ambitious, world-class performance on dynamic locomotion and manipulation tasks with physical hardware.
  • Drive the entire development cycle, from prototyping in simulation to robustly transferring and fine-tuning policies on the robot.
  • Mentor junior engineers by providing technical guidance, conducting insightful code reviews, and sharing best practices in reinforcement learning and software development.

Matching Summary

Implement and deploy state-of-the-art RL algorithms to achieve ambitious, world-class performance on dynamic locomotion and manipulation tasks with physical hardware.

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

Nice-to-have

  • human-centered robotics company
  • cutting edge of embodied AI
  • passion for real-world hardware

Key Requirements

  • 5+ years with common RL frameworks
  • 2+ years industry experience 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

Cover Letter