At-Home Video Recorder (Household Activities)

You will record synchronized first-person video of assigned household chores and physical tasks. The footage helps AI systems learn how people interact with everyday physical environments.

You will use a compatible smartphone and wearable head strap, follow instructions for framing and submitting footage, and complete repetitive movements safely while keeping recording quality consistent.

• Record household chores and other assigned physical tasks from home.
• Use a compatible smartphone with a wearable head strap for hands-free recording.
• Follow project instructions for framing, recording, and submitting video.
• Maintain consistent recording quality during repetitive movement tasks.

This is a remote, part-time contractor role open to candidates in the United States, with specific state restrictions. You must have the required equipment, be comfortable recording hands-free, and be able to perform the assigned movements safely.

• Pay: $15 per hour of qualifying recorded video.
• Bonus: Receive a $20 signing bonus after completing 20 hours of work.
• Equipment reimbursement: Receive reimbursement for the required head strap after completing 20 hours of work.
• Location: Open to candidates in the United States except Arizona, California, Colorado, Connecticut, the District of Columbia, Hawaii, Maine, New Jersey, Oregon, Rhode Island, and Washington.
• Language: English fluency required.
• Phone: Own an iPhone 12 or later, Google Pixel 6 through 9, or Samsung Galaxy S21 or later.
• Requirements: Be comfortable wearing phone-mount equipment, complete repetitive movements safely, and be eligible to work in the United States.

You apply here in about two minutes and finish on the hiring platform. The next step is a short AI interview (technical roles include a coding challenge). Passing it is how you qualify for paid tasks, so take it soon after you are invited.

AI training work uses human-created examples to help artificial intelligence systems learn from real-world information. Video contributors capture useful actions and interactions so models can better understand physical environments, and careful work is valued because consistent data improves model performance.