Dexmate
Reinforcement learning engineer
Santa Clara Office
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About the role
- We're seeking Reinforcement Learning experts to develop and deploy cutting-edge RL algorithms that enhance our robots' capabilities.
Responsibilities
- Develop and optimize RL training pipelines in both simulation and real-world environments
- Collaborate with robotics engineers to integrate RL models into production systems
Requirements
- Hands-on experience with robotics systems (simulation or real robots)
- Proven track record applying RL to manipulation, locomotion, or navigation tasks
- Strong understanding of robot kinematics, dynamics, and control
Nice to have
- 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.)
Benefits
- Design and implement reinforcement learning algorithms for various robotics tasks
- Scale training infrastructure for efficient learning across multiple robots
- Strong experience with reinforcement learning (PPO, SAC, TD3, DDPG, etc.)
- Proficiency in Python and deep learning frameworks (PyTorch, TensorFlow, JAX)
- Experience with GPU-based simulation such as Isaac Gym, Isaac Lab, SAPIEN, etc.
Company info
- Our mission is to democratize robotics by lowering the barrier to entry, delivering a plug-and-play platform for developers, researchers, and enterprises, and cultivating an open ecosystem that accelerates the evolution of physical AI.
- Dexmate is building the foundation for physical AI - a unified platform that combines high-quality robotic hardware with a universal Physical AI OS, making robots as easy to build and deploy as software.
This listing is sourced directly from Dexmate's careers page and normalized into a canonical job model.