Robot Operator

Physical Intelligence Physical Intelligence · AI Frontier · San Francisco, CA · Operations

This role involves teleoperating robotic arms to collect high-quality demonstration data for training foundation models for physical world AI. The operator will perform various tasks, maintain data quality, and meet collection metrics. It's a hands-on, metrics-driven position focused on generating training data for AI-powered robots.

What you'd actually do

  1. Teleoperate robotic arms through a variety of tasks using our intuitive control systems
  2. Either lead robot movements with your arms (the robot mirrors your actions) or guide robots using specialized controllers
  3. Complete diverse tasks ranging from household activities like folding laundry to complex assembly work
  4. Maintain high standards for data quality and consistency across all demonstrations
  5. Meet established metrics for data collection volume and quality during your shift

Skills

Required

  • Ability to stand at a workstation for 8-hour shifts
  • Full use of both arms and hands for robot control
  • Good hand-eye coordination and manual dexterity
  • Attention to detail for quality control
  • Meticulous attention to detail
  • Good manual dexterity and hand-eye coordination
  • Enjoys repetitive, precision-focused work
  • Thrives in fast-paced, metrics-driven environments

Nice to have

  • Experience with hands-on technical work, lab environments, or precision tasks
  • Interest in AI, robotics, and cutting-edge technology
  • Strong attention to detail and quality focus
  • Excited about contributing to breakthrough AI research
  • Collaborative mindset and strong work ethic
  • Experience with robotics systems or automation
  • Background in manufacturing, assembly, or laboratory work
  • Familiarity with AI/ML concepts
  • Gaming or simulation experience with controllers

What the JD emphasized

  • metrics-based role
  • repetitive task execution
  • quality of data collection is extremely important
  • Meticulous attention to detail—data quality is crucial for AI training
  • Good manual dexterity and hand-eye coordination
  • Enjoys repetitive, precision-focused work
  • Thrives in fast-paced, metrics-driven environments

Other signals

  • robotics
  • foundation models
  • training data
  • demonstration data
  • teleoperate robotic arms