Humanoid Robotic Engineer

Hyphen Partners

Boston, United States
On-site
Model predictive control (mpc)
Whole-body control expertise
Reinforcement learning policy training
The role focuses on developing sophisticated control algorithms specifically for bipedal locomotion and manipulation tasks

Job Summary

  • The role focuses on developing sophisticated control algorithms specifically for bipedal locomotion and manipulation tasks.
  • Candidates will train Reinforcement Learning policies in simulation environments before deploying them onto physical robotic hardware.
  • Success requires conducting sim-to-real transfers and analyzing detailed gait and kinematics telemetry data.

Matching Summary

The role focuses on developing sophisticated control algorithms specifically for bipedal locomotion and manipulation tasks.

Skills & Requirements

Must-have

  • Model Predictive Control (MPC)
  • Whole-Body Control expertise
  • Reinforcement Learning policy training
  • NVIDIA Isaac Sim or MuJoCo simulation
  • Sim-to-real transfer implementation

Nice-to-have

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

Key Requirements

  • Strong background in Model Predictive Control
  • Extensive experience with robotic simulation environments
  • Familiarity with modern RL frameworks

Work Rights

Not specified

Tailored Resume

Cover Letter