Apptronik
Senior Reinforcement Learning Engineer
Sunnyvale, CA · Senior
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About the role
- The Senior Reinforcement Learning Engineer is a key, hands-on role focused on achieving state-of-the-art performance on our humanoid robots.
- As a senior member of the team, this individual will also be responsible for mentoring junior engineers, elevating the team's overall technical capabilities through their guidance and expertise.
- ESSENTIAL DUTIES AND RESPONSIBILITIES or KEY ACCOUNTABILITIES
Responsibilities
- This engineer will leverage their deep expertise in RL to solve critical locomotion and manipulation challenges and deliver breakthrough results on physical hardware.
- Implement and deploy state-of-the-art RL algorithms to achieve ambitious, world-class performance on dynamic locomotion and manipulation tasks with physical hardware.
- Drive the entire development cycle, from prototyping in simulation to robustly transferring and fine-tuning policies on the robot.
- Collaborate closely with the robotics and hardware teams to diagnose system-level issues and co-develop solutions that enable more complex learned behaviors.
- Apptronik is a human-centered robotics company developing AI-powered robots to support humanity in every facet of life.
Requirements
- Deep, hands-on expertise (5+ years) with common RL frameworks (e.g., PyTorch, JAX) and high-fidelity physics simulators (e.g., MuJoCo, IsaacGym)
- Mastery of Python for rapid prototyping and training, alongside strong proficiency in C++ for developing performant, deployable code.
- Must be able to lift 15 pounds at times
Nice to have
- A PhD or MS in Computer Science, Robotics, or a related field, with 2+ years industry experience strongly preferred.
- A strong publication record in relevant conferences or journals (e.g., CoRL, RSS, ICRA) is a significant plus.
Compensation
- The annual compensation for this position is $230,000 - $260,000 (USD)
Benefits
- Our flagship humanoid robot, Apollo, is built to collaborate thoughtfully with people, starting with critical industries such as manufacturing and logistics, with future applications in healthcare, the home, and beyond.
- The primary focus of this role is to rapidly implement, iterate, and deploy advanced learning algorithms to push the boundaries of what our robots can do.
- Develop and refine motion retargeting pipelines to translate human demonstration data (mocap, teleoperation) into robust reference trajectories for reinforcement learning.
Company info
- Analyze and present hardware results to guide future technical directions and demonstrate progress on key company objectives.
This listing is sourced directly from Apptronik's careers page and normalized into a canonical job model.