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Senior Reinforcement Learning Engineer

1 month, 2 weeks ago
United States
Full-time
Senior
AI Research Scientist
Software Development
C++ Python PyTorch Reinforcement Learning
Apply Now
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
View All Jobs 65

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

Apply Now

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