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This listing was closed on Aug 22, 2026.
Browse Open JobsAI Training Infrastructure Engineer – Humanoid Whole Body Control
Summary by AIEngineer.careers
AI Training Infrastructure Engineer – Humanoid Whole Body Control is a AI Infrastructure Engineer role (full-time). with Figure. in SAN JOSE, US. Compensation shown: $150K–$300K. Imported listing (source: jobs-radar.com). Apply on the employer's site (jobs-radar.com).
Imported listing (source: jobs-radar.com) · Apply on jobs-radar.com
SAN JOSE · US
$150K–$300K
Full-time
SENIOR
The sections below reproduce the third-party job description for reference. AIEngineer.careers does not write or control this text.
Imported job description
Sourced from jobs-radar.com
Figure is seeking an AI Training Infrastructure Engineer to own the training and deployment backbone for RL-based whole-body control systems on humanoid robots. The role involves scaling simulation, data pipelines, and tooling to accelerate policy iteration and deployment. Based in San Jose, CA with in-office collaboration.
Responsibilities
- Own and scale the infrastructure used to train whole-body control policies (simulation, data pipelines, orchestration, visualizations)
- Design fast, reliable, and configurable systems for controls engineers
- Ensure high cluster utilization and minimal downtime
- Evaluate and integrate physics engines (e.g., NVIDIA PhysX, MuJoCo, Warp, PyBullet)
- Optimize hyperparameters and infrastructure for training speed and efficiency
- Build robust tooling for training → validation → deployment pipeline
Requirements
- Strong software engineering fundamentals with production experience in Python and PyTorch
- Experience building or scaling training infrastructure for robotics, control systems, or large-scale ML workloads
- Familiarity with physics simulation tools (e.g., NVIDIA PhysX, MuJoCo, Warp, PyBullet)
Figure
San Jose · US · 527+ employees
Figure is an AI robotics company focused on developing general-purpose autonomous humanoid robots. The company aims to address labor shortages by deploying robots capable of supporting tasks in manufacturing, logistics, warehousing, and retail.
