Reinforcement Learning Systems Engineer
T
Tyson Jay
📍 Singapore, Singapore, Singapore
Job Description
Responsibilities
- Develop and iterate on locomotion controllers and motion policies for a legged platform
- Train and evaluate policies in simulation across walking, recovery, stair climbing, and load-bearing behaviors
- Design reward functions, curriculum schedules, and training infrastructure for real-world robustness
- Drive systematic sim-to-real transfer and hardware iteration
- Integrate locomotion outputs with the broader autonomy stack
- Collect and analyze hardware telemetry to guide policy improvement
Requirements
- Strong foundations in reinforcement learning, optimal control, and rigid body dynamics
- Hands-on experience training or deploying locomotion and motion control policies on physical legged robots, gained through industry or research work
- Proficient in Python, with strong JAX or PyTorch experience
- Experience with physics simulation e...