Ai Training Infrastructure Engineer – Humanoid Whole Body Control

Figureai

San Jose, CA, United States
Base: $200,000 - $300,000 annually; bonus/equity: ...
On-site
Python and pytorch production experience
Physics simulation tools like physx or mujoco
Reinforcement learning and policy distillation
The role involves owning the training and deployment backbone for RL-based whole-body control systems for humanoid robots

Job Summary

  • The role involves owning the training and deployment backbone for RL-based whole-body control systems for humanoid robots.
  • Engineers will design fast, reliable, and highly configurable systems to ensure high cluster utilization and accelerate iteration cycles.
  • Candidates must build robust tooling to transition policies from training through validation to deployment on actual hardware.

Matching Summary

The role involves owning the training and deployment backbone for RL-based whole-body control systems for humanoid robots.

Salary

Base: $200,000 - $300,000 annually; Bonus/Equity: Not specified; Benefits: Not specified

Skills & Requirements

Must-have

  • Python and PyTorch production experience
  • Physics simulation tools like PhysX or MuJoCo
  • Reinforcement learning and policy distillation
  • Dynamics, controls, and robotics systems knowledge
  • Scaling training infrastructure for ML workloads

Nice-to-have

  • Humanoid or legged robot control experience
  • Background in distributed systems and schedulers
  • Deploying ML models to real-world hardware
  • Modeling contact interactions in simulation
  • Ownership mindset for critical team systems

Key Requirements

  • Strong software engineering fundamentals with Python/PyTorch
  • Experience building or scaling training infrastructure
  • Working knowledge of dynamics and controls systems

Work Rights

Not specified

Tailored Resume

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