The work
You will review annotated video data used to train AI systems. The work involves making careful visual judgments, checking annotations against project guidelines, and documenting issues clearly across a large volume of video content.
- Review and quality-check video annotations against established guidelines.
- Check the accuracy, completeness, and consistency of annotated video data.
- Identify, document, and correct annotation issues.
- Decide whether videos and annotations meet required quality standards.
- Give clear feedback on recurring errors and unclear cases.
- Follow established workflows, collaborate on quality questions, and meet project deadlines.
What it pays and takes
The listing describes compensation as competitive but does not provide a specific rate. This is a remote, part-time contract role with flexible working hours.
- Pay: Competitive compensation; no specific rate is provided.
- Schedule: 20 or more hours per week with flexible working hours.
- Availability: Weekend work may be required when project timelines are tight.
- Location: Open worldwide and fully remote.
- Language: Professional fluency in English.
- Experience: At least three years working on data annotation projects.
- Required background: Experience with video annotation or video quality assurance, including reviewing, validating, or auditing annotated datasets.
- Skills and equipment: Strong visual attention to detail, analytical skills, consistent use of detailed quality guidelines, reliable internet access, and a suitable computer.
How it works
Apply on OpenTrain with your resume, then complete the application on the hiring site. OpenTrain is where people find AI training and data-labeling roles and start their applications.
About AI training work
AI training is the human work behind systems that learn from examples, including reviewing and labeling images and video. People with experience in careful quality review help make those examples accurate and consistent.