Figure

Figure

Project Coordinator, Data Quality

San Jose, CA · Full-time

Sponsorship not specified$35k-$40kDetected 1 day ago
Machine LearningLLMsRoboticsLeadership

About the role

  • The goal of the company is to ship humanoid robots with human level intelligence.
  • The US base salary range for this full-time position starts at $40/hr.

Responsibilities

  • Own review guidelines and acceptance criteria for your project
  • Write and maintain project-level SOPs
  • Manage direct reports where applicable, including structured performance reviews.
  • Design project-specific training materials and calibration exercises.
  • Own review guidelines and acceptance criteria for your project; handle escalated edge cases that fall outside existing guidance.
  • Write and maintain project-level SOPs; update them through post-project retros.

Requirements

  • 4+ years of experience in data quality, data labeling operations, or content/data review roles, with demonstrated ownership of a project or workstream end-to-end.
  • Experience writing review guidelines, acceptance criteria, or SOPs that other people executed against.
  • Experience running audit or QA cycles and translating findings into process or guideline changes.
  • Comfort working directly with engineering or ML stakeholders to translate technical requirements into operational guidance.
  • Experience managing vendor relationships, including SLA communication.

Nice to have

  • Experience with golden set / ground truth construction.
  • Background in robotics, autonomous systems, LLM or physical AI data.
  • Experience designing training or calibration programs for review teams.
  • This information will be shared if an employment offer is extended.

Skills

  • The pay offered for this position may vary based on several individual factors, including job-related knowledge, skills, and experience.

Compensation

  • The US base salary range for this full-time position starts at $40/hr.

This listing is sourced directly from Figure's careers page and normalized into a canonical job model.