Robotics Reinforcement Learning Engineer

Company Background: At Human in Motion Robotics (HMR), based in Vancouver, Canada, we’re redefining mobility with advanced bipedal and humanoid robotic systems. Our mission is to enhance human potential through intelligent assistive and autonomous solutions that improve mobility, safety, and independence.

HMR has developed the world’s most advanced wearable bipedal exoskeleton and, with a multidisciplinary team of innovators, engineers, and visionaries, is leading the next generation of robotics, scaling from R&D to full-scale production.

Job Description: We’re seeking a Robotics Reinforcement Learning Engineer to contribute to the development of learned locomotion behaviors-from walking and balancing to transitions and terrain adaptation-in simulation and on physical hardware.

As part of our growing AI & Robotics team, you’ll help build reinforcement learning systems that enable natural, adaptive, and robust locomotion in humanoid and exoskeleton platforms.

Responsibilities: The candidate’s main responsibilities are:

• Design and train end-to-end reinforcement learning policies for bipedal locomotion in high-fidelity simulations.
• Contributes to the development and optimization of system models, and domain randomization for sim-to-real transfer.
• Use large-scale parallel simulation to develop generalized policies.
• Develop tools and workflows for RL pipeline automation.
• Integrate simulation-based test cases into the CI/CD pipeline for continuous regression testing and motion policy validation.
• Collaborate with controls, hardware, and biomechanics teams to ensure scalable deployment of learned policies on real robotic systems.

Required skills/Qualifications:

• M.Sc. or Ph.D. in Robotics, Machine Learning, Computer Science, or a related field.
• Experience with robotic system simulation using MuJoCo, Isaac Gym, Bullet, or similar platforms.
• Proficient in C++ and Python, with strong software development and debugging skills.
• Hands-on experience with reinforcement learning frameworks (e.g., RLlib, Stable-Baselines, custom PyTorch-based environments).
• Solid understanding of robotics kinematics/dynamics, control systems, and actuator modeling.
• Experience working with legged robots or exoskeleton platforms, either in simulation or physical environments.

Preferred and Plus skills:

• Experience with sim-to-real transfer techniques, including domain randomization, closed-loop torque control, and curriculum learning.
• Prior work training RL policies that track human reference motions or obey stylistic constraints.
• Experience with zero-shot deployment of policies on real-world systems.
• Contributions to open-source robotics or ML projects (please include links to GitHub, papers, or videos).

Who You Are:

• Self-motivated and proactive, with a strong desire to learn and grow.
• A “get-things-done” attitude with the ability to manage shifting priorities.
• Thrive in collaborative, cross-functional teams.
• Excited about working on complex, impactful technologies that move the world forward.

Why Join Us?

• Be part of a mission-driven team building the future of mobility.
• Access production-ready and advanced humanoid hardware and software platforms.
• Collaborative culture that encourages innovation and creativity.
• Opportunities for growth, leadership, and specialization.
• Competitive salary and benefits package including paid time off, employee stock options, and extended health care.
• A chance to leave your mark on one of the most exciting fields in technology.

How to Apply: The description of the role above is what we believe an exemplary candidate could look like, if you have related experience but don’t necessarily meet all the requirements, please apply! If you are ready for an exciting opportunity with a fast-growing start-up on a mission to change people’s lives, submit your resume and portfolio outlining your experience and interest in the role.

HMR is an inclusive and equal opportunity employer. If you require accommodation during the recruitment process, please let us know and we’ll be happy to support your needs.