User Research

Senior Reinforcement Learning Engineer

Lead senior-level reinforcement learning work for Apollo humanoid movement and manipulation in Austin.

What the role actually is

Apptronik is hiring a senior reinforcement learning engineer in Austin. The role focuses on applying RL to locomotion and manipulation challenges for humanoid robots, with an explicit expectation that results reach physical hardware.

This is a senior individual-contributor role with mentoring responsibilities, not a generic research label attached to a software job.

What you would work on

  • Implement and iterate on RL methods for humanoid robot behavior
  • Transfer policies from simulation to physical robot tests
  • Improve training infrastructure for high-throughput experimentation
  • Mentor engineers working on robot-learning systems

What they are asking for

  • Deep reinforcement learning experience in robotics or embodied systems
  • Ability to debug model behavior across simulation and hardware
  • Strong technical judgment around training pipelines and evaluation
  • Experience guiding other engineers without losing hands-on velocity

Why this one is worth a look

Senior robot-learning roles are valuable when they still stay close to the robot. Apptronik's posting frames the job around actual locomotion and manipulation results, which is the right center of gravity for a humanoid RL role.

About Apptronik

Austin humanoid robotics company building general-purpose robots for industrial and commercial work.

Visit Apptronik

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