Reinforcement learning engineer

dexmate· Engineering
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📍 Santa Clara OfficeFullTime

About this role

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. Today, robotics is fragmented, slow, and closed: most builders are forced to reinvent the same stack again and again, and most ideas never make it past the prototype stage. We exist to change that. 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. If you want to help shape the next layer of human capability — and believe the future of robotics should be built together, not in isolation — we'd love to build it with you.

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.)

Frequently Asked Questions

Is the salary disclosed for the Reinforcement learning engineer position at dexmate?
The salary for this Reinforcement learning engineer role at dexmate is not publicly listed. Click "Apply Now" to learn more about the compensation package on their official careers page.
Where is the Reinforcement learning engineer position at dexmate located?
This Reinforcement learning engineer role at dexmate is based in Santa Clara Office. The position is listed as on-site or hybrid. Check the full job description or apply directly to confirm the work arrangement.
Is the Reinforcement learning engineer role at dexmate full-time or part-time?
This is listed as a FullTime position. It is posted as a Reinforcement learning engineer role in the Engineering department at dexmate.
Which team or department does the Reinforcement learning engineer at dexmate belong to?
This Reinforcement learning engineer position is part of the Engineering department at dexmate. See the full job description for more information about the team structure and responsibilities.
How do I apply for the Reinforcement learning engineer position at dexmate?
Click the "Apply Now" button on this page. You will be redirected to dexmate's official application portal hosted on ashby where you can submit your application directly.
When was the Reinforcement learning engineer job at dexmate posted?
This Reinforcement learning engineer position at dexmate was posted on Jan 19, 2026. Apply as soon as possible — early applications are often reviewed first.
Reinforcement learning engineer
dexmate
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