Senior RL Engineer for Humanoid Robots & Real-World Systems

Apptronik; Sunnyvale, Northern (CA, KY); Hybrid; USD 170,000 - 230,000; Full time

Job summary

Apptronik is seeking a Senior Reinforcement Learning Engineer to advance state-of-the-art learning for our humanoid robotics platform. You will implement and optimize RL methods on physical hardware, mentor junior engineers, and help scale training pipelines from simulation to real robots.

You will work closely with robotics and hardware teams to push capabilities in locomotion and manipulation, shaping the trajectory of our AI-enabled robots.

Qualifications

• 5+ years hands-on RL experience with PyTorch or JAX.
• Proficient Python for prototyping; C++ for deployment.
• Experience with large-scale distributed training pipelines.
• PhD or MS in CS/Robotics preferred with 2+ years industry exp.
• Publication record in RL or robotics is a plus.

Responsibilities

• Implement and deploy state-of-the-art RL algorithms for locomotion and manipulation on hardware.
• Prototype in simulation and transfer policies to the robot; iterate and refine.
• Scale RL training pipelines for high-throughput simulation and distributed training.
• Mentor junior engineers through code reviews and knowledge sharing.
• Collaborate with robotics and hardware teams to diagnose system issues.
• Analyze hardware results to guide future technical directions.
• Develop motion retargeting to translate human demonstrations into reference trajectories.

Skills

Reinforcement learning

Python

C++

Distributed training

Robot dynamics

Mentoring

Education

MS/PhD in CS or Robotics

Tools

PyTorch

JAX

MuJoCo

IsaacGym

Job description

Apptronik is seeking a Senior Reinforcement Learning Engineer to advance state-of-the-art learning for our humanoid robotics platform. You will implement and optimize RL methods on physical hardware, mentor junior engineers, and help scale training pipelines from simulation to real robots.

You will work closely with robotics and hardware teams to push capabilities in locomotion and manipulation, shaping the trajectory of our AI-enabled robots.