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Physical Intelligence

Develops AI-driven robotic systems for industry

Robot Operator

Applied Machine LearningConfirmed live in the last 24 hours
Full-timeSan Francisco, CA, USA$25 /hrIn-person

About the Job

Requirements

  • Experience with hands-on technical work, lab environments, or precision tasks.
  • 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.
  • Ability to meet data collection goals throughout each shift in a repetitive, metrics-based role.

Responsibilities

  • Teleoperate robotic arms through a variety of tasks using the control systems.
  • Lead robot movements with arm movements so the robot mirrors the operator, or guide robots using specialized controllers.
  • Complete diverse tasks, including household activities and complex assembly work.
  • Maintain high standards for data quality and consistency across demonstrations.
  • Meet established metrics for data collection volume and quality during each shift.
  • Review and annotate videos of robot task performances using computer interfaces.
  • Provide detailed feedback on robot performance and data quality.
  • Assist with equipment setup and basic office tasks as needed.
  • Participate in process improvements to enhance data collection efficiency.

Desired Qualifications

  • Experience with robotics systems or automation.
  • Background in manufacturing, assembly, or laboratory work.
  • Familiarity with artificial intelligence and machine learning concepts.
  • Gaming or simulation experience with controllers.

About the Company

Physical Intelligence

Develops AI-driven robotic systems for industry

Physical Intelligence develops AI-powered robotic systems by creating general-purpose AI models and learning algorithms to control physically actuated devices in the real world, serving industries like manufacturing, healthcare, and logistics. Its approach uses foundational models and learning-based control software that runs on robots to sense, decide, and act in real environments, often integrated with hardware and partner networks. The company differentiates itself by focusing on foundational AI methods for physical robotics and partnering with high-profile investors to support both R&D and commercialization across multiple industries. Its goal is to bring AI-driven robotic systems into real-world operations to boost efficiency and productivity through scalable, learnable robotics.

Company size
201-500
Company stage
Late Stage VC
Total funding
$2.1B
Headquarters
San Francisco, CA
Founded
2024

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