Robotics Data Collection Operator

OpenTrain is hiring a Robotics Data Collection Operator to help collect real-world recordings and observations for robotic intelligence systems. You will work onsite in a San Francisco lab, using a handheld UMI gripper to complete repeated household manipulation tasks.

• Use a handheld gripper to pick up objects, open containers, and complete simple household tasks.
• Follow detailed written instructions and collection procedures during repeated attempts.
• Reset physical environments between attempts and check each data submission for quality.
• Report hardware problems, unclear instructions, and damaged or incomplete recordings.
• Record observations, suggest process improvements, and coordinate with project leads and other contributors.
• Stay accurate and focused during extended periods of repetitive physical activity.

What it pays and takes

This is an entry-level, part-time contractor role. Previous robotics or AI experience is not required, but you should be comfortable with hands-on work, basic hardware interfaces, and minor technical troubleshooting.

• Location: Onsite in San Francisco, United States.
• Language: English.
• Hours: 20 or more hours per week.
• Employment: Contractor and part time.
• Pay: The role description lists $10-$20 per hour, while the structured listing details show $30 per hour. Confirm the applicable rate when applying.
• Bring fine motor control, dexterity, precision, and strong attention to detail.
• Follow complex step-by-step instructions reliably and consistently.
• Be punctual, accountable, and able to communicate clearly in writing and conversation.
• Experience in physical operations, object handling, warehouse work, gaming, gig work, or student projects may help, but is not required.

How it works

Apply on OpenTrain with your resume, then complete the application on the hiring site.

About AI training work

AI training work uses human-collected and reviewed examples to help artificial intelligence systems learn how to respond to the real world. People are paid for careful, consistent work because the quality of these examples affects how well AI systems perform.