Senior RL Engineer: Humanoid Robotics on Real Hardware

Grit Ventures; Austin (TX); On-site; USD 150,000 - 210,000; Full time

Job summary

Apptronik is seeking a Senior Reinforcement Learning Engineer to drive state-of-the-art RL solutions for locomotion and manipulation on real humanoid robots. You will prototype in simulation and deploy policies on physical hardware, working closely with robotics and hardware teams to push capabilities and reliability.

The role emphasizes mentoring junior engineers, advancing core infrastructure for high-throughput simulation, and delivering measurable progress toward product-ready motion and

Qualifications

• PhD or MS in CS, robotics or related field; 2+ years industry experience preferred.
• Proven track record deploying learning-based policies on physical robots.
• Strong mentoring ability and publication history is a plus.

Responsibilities

• Implement and deploy RL algorithms for locomotion and manipulation on hardware.
• Prototype in simulation and transfer policies to the robot hardware.
• Optimize RL training pipelines for fast iteration and scale.
• Mentor junior engineers and share best practices in RL and software.
• Collaborate with robotics and hardware teams to diagnose system issues.
• Analyze hardware results to guide future directions.

Skills

RL frameworks PyTorch/JAX

Python programming

C++ development

Distributed training

Robotics control theory

Education

PhD in CS/Robotics

MS in CS/Robotics

Tools

MuJoCo

IsaacGym

Job description

Apptronik is seeking a Senior Reinforcement Learning Engineer to drive state-of-the-art RL solutions for locomotion and manipulation on real humanoid robots. You will prototype in simulation and deploy policies on physical hardware, working closely with robotics and hardware teams to push capabilities and reliability.

The role emphasizes mentoring junior engineers, advancing core infrastructure for high-throughput simulation, and delivering measurable progress toward product-ready motion and