Remote Household Task Video Recorder

As a Remote Household Task Video Recorder, you will play a crucial role in advancing robotics and machine learning by capturing high-quality synchronized motion and video data from your home. This position is ideal for detail-oriented and tech-savvy individuals looking to blend technology with everyday activities.

• Capture synchronized motion data using your smartphone’s IMU sensors while performing designated household tasks.
• Record high-fidelity video footage alongside sensor data to enhance the accuracy and reliability of datasets.
• Adhere to strict technical protocols to ensure quality submissions, precise labeling, and data determinism.
• Deliver a minimum of 10 hours of approved video data each week, meeting all project requirements.
• Engage proactively with the team to clarify assignment guidelines and provide actionable feedback on data processes.
• Organize, prepare, and submit data in accordance with project milestones and quality standards while meeting deadlines.
• Complete necessary device compatibility checks and participate in a custom AI-enabled interview process.

• Proven experience following rigorous protocols and technical procedures in a professional environment.
• Exceptional written and verbal communication skills for clear documentation and remote collaboration.
• Strong proficiency in using smartphones and mobile applications for data collection tasks.
• Physical ability to safely perform repetitive household movement tasks.
• Demonstrated commitment to delivering reliable and consistent output in a time-sensitive setting.
• Access to a compatible smartphone for high-quality IMU and video data capture.

Contract position with remote work flexibility.

$13 per hour.

Must be eligible to work from one of the following U.S. states: Alabama, Georgia, Idaho, Indiana, Iowa, Kansas, Kentucky, Louisiana, Mississippi, New Hampshire, North Carolina, North Dakota, Oklahoma, Pennsylvania, South Carolina, Tennessee, Texas, Utah, or Wisconsin.

• Background in robotics, kinesiology, human motion analysis, or sensor-based data collection projects.
• Experience in structuring and labeling large datasets for machine learning applications.
• Familiarity with activity recognition or activity segmentation protocols.