Humanoid Robotic Engineer

Hyphen Connect

Seattle, United States
On-site
Bipedal locomotion and manipulation
Reinforcement learning policy training
Model predictive control expertise
The role focuses on designing sophisticated control algorithms to enhance humanoid robotic performance in both simulation and real-world settings

Job Summary

  • The role focuses on designing sophisticated control algorithms to enhance humanoid robotic performance in both simulation and real-world settings.
  • Candidates will be responsible for training Reinforcement Learning policies and conducting sim-to-real transfers on physical hardware.
  • Strong expertise in Model Predictive Control and Whole-Body Control is essential for developing advanced bipedal locomotion systems.

Matching Summary

The role focuses on designing sophisticated control algorithms to enhance humanoid robotic performance in both simulation and real-world settings.

Skills & Requirements

Must-have

  • Bipedal locomotion and manipulation
  • Reinforcement Learning policy training
  • Model Predictive Control expertise
  • Whole-Body Control implementation
  • NVIDIA Isaac Sim or MuJoCo simulation

Nice-to-have

  • Real-world hardware deployment experience
  • Gait and kinematics telemetry analysis
  • Modern RL framework familiarity

Key Requirements

  • Extensive experience with robotic simulation environments
  • Strong background in MPC and Whole-Body Control

Work Rights

Not specified

Tailored Resume

Cover Letter