Reinforcement Learning Systems Engineer

Tyson Jay • Singapore, Singapore • Posted June 12, 2026

About the Role

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...