Head of Robotic Locomanipulation & Team Delivery

Humanoid

California

On-site

USD 300,000 - 450,000

Full time

5 days ago
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Benefits offered by this job

Health coverage
23 days PTO
401(k) with match
Equity
Free daily lunch
Collaboration with top engineers
Influence product initiatives

Job summary

Humanoid is seeking a Director of Autonomy - Biped in California to lead a team focused on locomanipulation in homes and service settings. You will own the roadmap, hiring, and delivery while training policies and debugging the robot hands-on.

This role sits at the intersection of applied deep learning, robotics, and people leadership, collaborating with Controls and Core Technology to advance sim-to-real and base model development for bipedal dexterity.

Qualifications

  • 5+ years in robotics with shipped artifacts.
  • Experience leading 5+ engineers in applied robot learning.
  • Hands-on experience training and debugging policies recently.

Responsibilities

  • Own The Capability Roadmap: set priorities and deliverables with product.
  • Lead The Team: hire, mentor, and set engineering standards.
  • Co-Own The System 0/1 Interface: define policy commands and diagnose failures.
  • Partner On Data Strategy: specify data needs and supervise data collection.
  • Drive Sim-To-Real Transfer: coordinate RL training in simulation and real-world transfer.
  • Shape Base Model Development: integrate embodiment requirements into pretraining.
  • Inform Hardware Design: feed findings to future hardware teams.
  • Report On Progress: communicate metrics and failure analyses to leadership.

Skills

Robot learning
People management
Policy training
Data curation
RL / policy deployment
Teleoperation basics
PyTorch / JAX

Job description

Humanoid is seeking a Director of Autonomy - Biped in California to lead a team focused on locomanipulation in homes and service settings. You will own the roadmap, hiring, and delivery while training policies and debugging the robot hands-on.

This role sits at the intersection of applied deep learning, robotics, and people leadership, collaborating with Controls and Core Technology to advance sim-to-real and base model development for bipedal dexterity.

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