Robotics Teleoperator — Onsite Data Collection (SF, 6w)

Welocalize; San Francisco (CA); On-site; USD 41,000 - 58,000; Full time

Job summary

Welocalize in San Francisco is seeking data collection operators to support physical AI programs. You will operate physical AI data collection systems using teleoperation tools and guided interfaces to produce high-quality real-world data used to train AI models.

This hands-on, execution-focused role involves working with real hardware in structured environments, following defined scenarios, and helping shape how robots learn.

Qualifications

• Bachelor’s degree or equivalent work experience.
• Experience with gaming, simulation tools, or technical systems is a plus.
• Strong hand-eye coordination and spatial awareness.
• Comfortable using controllers, keyboards, or specialized interfaces for extended periods.
• Basic computer skills, including PC and Linux troubleshooting.
• Working knowledge of MS Office and Google Drive.
• Ability to follow detailed procedures with high accuracy.
• Clear written and verbal communication skills.

Responsibilities

• Operate robotic systems through VR or headset controls, robotic interfaces, and other teleoperation equipment.
• Execute data collection tasks to established procedures, maintaining consistency, accuracy, and data quality.
• Troubleshoot basic hardware and connectivity issues.
• Document issues and elevate technical failures to the appropriate teams.
• Adapt to changes in workflows, equipment configurations, and procedures.
• Comply with safety, security, and operational requirements.

Skills

Hand-eye coordination

Spatial awareness

Attention to detail

Procedural following

Written and verbal communication

Education

Bachelor’s degree or equivalent work experience

Job description

Welocalize in San Francisco is seeking data collection operators to support physical AI programs. You will operate physical AI data collection systems using teleoperation tools and guided interfaces to produce high-quality real-world data used to train AI models.

This hands-on, execution-focused role involves working with real hardware in structured environments, following defined scenarios, and helping shape how robots learn.