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OpenTrain AIFor AI Companies

Robot Teleoperator (On-site)

Join OpenTrain as an on-site Robot Teleoperator in the US to operate robotic arms and humanoids using VR and leader-arm systems to collect 3D sensor demonstration data; part-time contractor role (20+ hrs/week) paid $30–$55/hr.

OpenTrain AI

Data Collection

Remote Hourly · $30–$55/hr

$30–$55/hr

Compensation

1 country

Eligibility

Entry

Experience

Jun 30, 2026

Posted

Open to applicants in

United States

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About OpenTrain

OpenTrain is the #1 platform for finding and building careers in AI training and data labeling. We help people discover projects, consolidate opportunities, and build a unified portfolio they control so they can grow durable freelance careers in the AI training industry.

Why AI training matters

AI training (data labeling and human demonstration work) is the human side of building intelligent systems. People prepare and review examples—images, video, audio, or robot demonstrations—that teach models how to act and perceive. This work is remote-friendly, flexible, and places contributors at the cutting edge of how AI systems are created.

The role

OpenTrain is recruiting for an on-site Robot Teleoperator to join a robotics operations team. This hands-on lab role uses teleoperation interfaces (leader-arm systems, VR headsets, controllers) to produce high-quality demonstration data for embodied AI and robotics research.

  • Employment type: Contractor, part-time (on-site in the United States).
  • Minimum weekly time: 20+ hours.
  • Data collected: 3D sensor demonstrations (DATA_COLLECTION).
  • / custom teleoperation systems.

What you'll do

You will operate robotic manipulators and humanoid robots and follow strict protocols to generate consistent demonstration datasets used to train next-generation embodied AI systems.

  • Operate robotic arms and humanoids with leader-arm systems, VR headsets, and handheld controllers.
  • Execute structured manipulation tasks to create repeatable, high-quality demonstration data.
  • Monitor sessions, report hardware or software issues, and help troubleshoot basic problems.
  • Set up workstations, position cameras and sensors, and keep the lab organized.
  • Adapt to new robot platforms and teleoperation interfaces as systems evolve.

Requirements

Candidates must meet the essential skills and be comfortable working in a hands-on lab environment for extended VR sessions.

  • Experience with VR systems (Meta Quest, Vision Pro, SteamVR, or comparable motion-control tech).
  • Strong hand-eye coordination and fine motor skills.
  • Comfortable learning new hardware and control interfaces quickly.
  • Basic troubleshooting ability and clear communication of technical issues.
  • Reliable, detail-oriented, and able to work extended VR sessions without loss of quality.

Helpful background

We value related experiences that make the work easier to learn and perform, though this is listed as an entry-level role.

  • Gaming experience requiring precise control (FPS, simulation, racing, VR).
  • Prior robotics, automation, or teleoperation exposure.
  • Comfortable in fast-paced R&D or AI robotics environments.
  • Interest in robotics, human-robot interaction, or embodied AI research.

Location, schedule, and compensation

This is an on-site position in the United States. The role is offered as a contractor, part-time assignment with a minimum commitment of 20 hours per week.

  • Pay: $30–$55 per hour (PAY_PER_HOUR).
  • Weekly commitment: 20+ hours/week (schedule variability depends on project needs).
  • Worksite: On-site lab at OpenTrain locations in the United States.

How to apply

If this role matches your skills and interests, apply through OpenTrain to submit your profile and experience. We recommend highlighting VR or teleoperation experience and any hands-on robotics or gaming background in your application.

  • Include examples of VR hardware used and typical session lengths you can sustain.
  • List any previous robotics or lab experience, even if informal (personal projects, clubs, or gaming).