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.
#J-18808-LjbffrSenior Reinforcement Learning Engineer in austin at Unknown Company
This position is listed as full time and onsite.