Humanoid RL Research Engineer: Sim2Real & Motion Learning

Halodi Robotics; San Carlos (CA); On-site; USD 120,000 - 180,000; Full time

Job summary

Halodi Robotics in California seeks a robotics ML engineer to develop sim2real reinforcement learning (RL) training pipelines for humanoid robots used in in-home settings. You will train and test robot policies via RL, aiming to optimize training pipelines for performance and speed, and model physical systems to close the gap between simulation and hardware.

Responsibilities include collecting and retargeting human motion data for RL pipelines, and supporting testing and debugging on both

Qualifications

• Master’s degree or foreign degree equivalent in Robotics, AI/Machine Learning, Mechanical or Electrical Engineering, Computer Science, or related field
• One year of experience in Robotics & Machine Learning occupation or related in the job offered

Responsibilities

• Develop sim2real RL training pipelines for humanoid robots.
• Train and test robot policies via reinforcement learning.
• Optimize training pipelines for performance and speed.
• Model physical systems including sensors and contacts to reduce sim-to-real gap.
• Collect, clean and retarget human motion data for RL training pipelines.
• Support test and debugging on simulation and hardware.

Skills

Reinforcement learning

Python

C++

Rigid body dynamics

Sim2real

Education

Master's degree

Tools

ROS

Gazebo

Job description

Halodi Robotics in California seeks a robotics ML engineer to develop sim2real reinforcement learning (RL) training pipelines for humanoid robots used in in-home settings. You will train and test robot policies via RL, aiming to optimize training pipelines for performance and speed, and model physical systems to close the gap between simulation and hardware.

Responsibilities include collecting and retargeting human motion data for RL pipelines, and supporting testing and debugging on both