Senior Reinforcement Learning Engineer

2 hours, 26 minutes ago
Full-time
Senior
Software Development
Apptronik

Apptronik

Apptronik develops versatile humanoid robots to tackle tasks humans prefer not to do, aiming to reshape existence and enhance universal quality of life.

Aerospace & Defense
51-250
Founded 2015
$23M raised

Description

  • Implement and deploy state-of-the-art reinforcement learning algorithms for locomotion and manipulation on physical hardware.
  • Drive the development cycle from simulation prototyping through policy transfer, fine-tuning, and deployment on the robot.
  • Optimize and scale the reinforcement learning training pipeline for faster iteration and high-throughput distributed training.
  • Mentor junior engineers through technical guidance, code reviews, and best practices in reinforcement learning and software development.
  • Collaborate with robotics and hardware teams to diagnose system-level issues and co-develop solutions for more complex learned behaviors.
  • Analyze and present hardware results to inform technical direction and support company objectives.
  • Develop and refine motion retargeting pipelines that convert human demonstration data into reference trajectories for reinforcement learning.

Requirements

  • 5+ years of hands-on experience with reinforcement learning frameworks such as PyTorch or JAX and simulators such as MuJoCo or IsaacGym.
  • Strong proficiency in Python for prototyping and training, and C++ for performant, deployable code.
  • Experience building or using large-scale distributed training pipelines and optimizing them for performance.
  • Strong theoretical understanding of modern reinforcement learning, including imitation learning, model-based RL, and sim-to-real transfer.
  • Strong intuition for robot dynamics and controls theory applied to learning-based approaches.
  • Results-oriented mindset with a passion for deploying complex algorithms on real-world hardware.
  • PhD or MS in Computer Science, Robotics, or a related field; 2+ years of industry experience strongly preferred.
  • Proven track record of deploying learning-based policies on physical robotic systems, especially legged robots or manipulators.
  • Experience mentoring or providing technical guidance to other engineers in a team environment.
  • Publication record in relevant conferences or journals such as CoRL, RSS, or ICRA is a significant plus.

Interested in this position?

Apply directly on the company website

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