Job Summary:
Apptronik is a human-centered robotics company developing AI-powered robots to support humanity in every facet of life. The Senior Reinforcement Learning Engineer will leverage their expertise in reinforcement learning to solve locomotion and manipulation challenges, mentor junior engineers, and implement advanced learning algorithms for the company's humanoid robots.
Responsibilities:
โข Implement and deploy state-of-the-art RL algorithms to achieve ambitious, world-class performance on dynamic locomotion and manipulation tasks with physical hardware.
โข Drive the entire development cycle, from prototyping in simulation to robustly transferring and fine-tuning policies on the robot.
โข Optimize and scale the RL training pipeline for faster iteration, contributing to core infrastructure for high-throughput simulation and distributed training.
โข Mentor junior engineers by providing technical guidance, conducting insightful code reviews, and sharing best practices in reinforcement learning and software development.
โข Collaborate closely with the robotics and hardware teams to diagnose system-level issues and co-develop solutions that enable more complex learned behaviors.
โข Analyze and present hardware results to guide future technical directions and demonstrate progress on key company objectives.
โข Develop and refine motion retargeting pipelines to translate human demonstration data (mocap, teleoperation) into robust reference trajectories for reinforcement learning.
Qualifications:
Required:
โข Deep, hands-on expertise (5+ years) with common RL frameworks (e.g., PyTorch, JAX) and high-fidelity physics simulators (e.g., MuJoCo, IsaacGym)
โข Mastery of Python for rapid prototyping and training, alongside strong proficiency in C++ for developing performant, deployable code.
โข Experience building or utilizing large-scale, distributed training pipelines and a strong intuition for their optimization.
โข A strong theoretical understanding of modern reinforcement learning, including deep expertise in areas like imitation learning, model-based RL, and sim-to-real transfer techniques.
โข A strong intuition for robot dynamics and controls theory, with the ability to apply these principles to guide and constrain learning-based approaches.
โข A results-oriented mindset with a passion for seeing complex algorithms work on real-world hardware.
โข A PhD or MS in Computer Science, Robotics, or a related field, with 2+ years industry experience strongly preferred.
โข A proven track record of successfully deploying learning-based policies on physical robotic systems, especially legged robots or manipulators.
โข Demonstrated experience mentoring or providing technical guidance to other engineers in a team environment.
โข A strong publication record in relevant conferences or journals (e.g., CoRL, RSS, ICRA) is a significant plus.
Company:
Apptronik is a robotics company that designs and builds humanoid robots for various real-world applications. Founded in 2016, the company is headquartered in Austin, USA, with a team of 51-200 employees. The company is currently Growth Stage.