Senior Reinforcement Learning Engineer

The Robot Age; Austin, Northern (TX, KY); Hybrid; USD 150,000 - 210,000; Full time

Job summary

Apptronik in Austin seeks a senior reinforcement learning engineer to advance humanoid robot behavior through deep RL; you will bridge simulation and real hardware, improving training pipelines and mentoring a small team of engineers.

The role emphasizes hands-on velocity with leadership responsibilities in a senior IC position focused on locomotion and manipulation challenges.

Qualifications

• 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.

Responsibilities

• 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.

Skills

Deep RL in robotics

Robotics systems

Simulation-to-hardware debugging

Training pipelines

Mentoring engineers

Job description

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.