Reinforcement learning engineer
Dexmate•Santa Clara, CA
11d
About The Position
We're seeking Reinforcement Learning experts to develop and deploy cutting-edge RL algorithms that enhance our robots' capabilities.
Requirements
- 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.
Nice To Haves
- 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.)
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
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What This Job Offers
Education Level
No Education Listed
Number of Employees
1-10 employees
