Senior Reinforcement Learning Engineer - Humanoid Robotics

Grit Ventures; Sunnyvale (CA); On-site; USD 170,000 - 210,000; Full time

Job summary

Apptronik is a human-centered robotics company accelerating AI-powered robots. We are seeking a Senior Reinforcement Learning Engineer to advance state-of-the-art locomotion and manipulation on our humanoid platform with real hardware.

You will prototype in simulation, transfer policies to the robot, and mentor junior engineers while solving complex learning problems. The role emphasizes robotics systems, distributed training, and collaboration with hardware teams to push performance and

Qualifications

• PhD or MS in CS, Robotics, or a related field with 2+ years industry experience.
• Proven track record deploying learning-based policies on physical robotic systems.
• Experience mentoring or guiding other engineers in a team.
• Strong publication record in venues like CoRL, RSS, ICRA is a plus.

Responsibilities

• Implement and deploy RL on locomotion and manipulation tasks with hardware.
• Prototype in simulation and transfer policies to the robot.
• Scale RL training pipelines for faster iteration and research infra.
• Mentor junior engineers and provide code reviews and guidance.
• Collaborate with robotics and hardware teams to solve system issues.
• Analyze hardware results to guide future technical directions.
• Develop motion retargeting pipelines from human data to RL trajectories.

Skills

PyTorch

JAX

Python

Distributed training

RL theory

Robot dynamics

Education

MS/PhD in CS/Robotics

Tools

MuJoCo

IsaacGym

Job description

Apptronik is a human-centered robotics company accelerating AI-powered robots. We are seeking a Senior Reinforcement Learning Engineer to advance state-of-the-art locomotion and manipulation on our humanoid platform with real hardware.

You will prototype in simulation, transfer policies to the robot, and mentor junior engineers while solving complex learning problems. The role emphasizes robotics systems, distributed training, and collaboration with hardware teams to push performance and