Reinforcement learning engineer

Role Overview

We're seeking Reinforcement Learning experts to develop and deploy cutting-edge RL algorithms that enhance our robots' capabilities.

Responsibilities

* Design and implement reinforcement learning algorithms for various robotics tasks

* Develop and optimize RL training pipelines in both simulation and real-world environments

* Collaborate with robotics engineers to integrate RL models into production systems

* Conduct experiments to evaluate and improve algorithm performance

* Scale training infrastructure for efficient learning across multiple robots

Required Qualifications

* Strong experience with reinforcement learning (PPO, SAC, TD3, DDPG, etc.)

* Hands-on experience with robotics systems (simulation or real robots)

* Proven track record applying RL to manipulation, locomotion, or navigation tasks

* Proficiency in Python and deep learning frameworks (PyTorch, TensorFlow, JAX)

* Strong understanding of robot kinematics, dynamics, and control

* Experience with GPU-based simulation such as Isaac Gym, Isaac Lab, SAPIEN, etc.

Preferred Qualifications

* Experience with distributed RL training systems

* Experience with sim-to-real transfer techniques

* Publications in robotics or RL conferences (CoRL, ICRA, RSS, NeurIPS, ICLR, ICML, etc.)