Video Data Annotation Specialist

The work

You will review short video and audio clips and label them using project guidelines. You will also assess AI-generated descriptions for accuracy and appropriateness, flag uncertain or inappropriate content, and explain possible errors or unclear points.

The role involves maintaining consistent annotations across substantial volumes of work, working independently as guidelines change, and protecting confidential project data. You may also collaborate remotely to clarify guidelines and improve processes.

• Review and annotate video and audio clips according to project guidelines.
• Evaluate AI-generated descriptions for accuracy and appropriateness.
• Flag uncertain or inappropriate content and explain inaccuracies or ambiguities.
• Maintain careful, consistent annotations across large volumes of work.
• Handle sensitive project information responsibly.

What it pays and takes

• Pay: $8 to $10 per hour.
• Work type: Remote contractor work with flexible scheduling.
• Language: Strong written English is required.
• Location: Open to candidates in Argentina, Bangladesh, Bahrain, Brazil, Chile, Colombia, Algeria, Egypt, Spain, Ghana, Greece, Indonesia, India, Italy, Jordan, Kenya, Kyrgyzstan, Kuwait, Kazakhstan, Lebanon, Sri Lanka, Morocco, Mexico, Malaysia, Nigeria, Oman, Peru, the Philippines, Pakistan, Palestine, Portugal, Saudi Arabia, Thailand, Tunisia, Taiwan, Uzbekistan, Vietnam, and South Africa.
• Experience with video or audio annotation, content labeling, or digital content moderation is preferred.
• Skills: Careful visual and audio judgment, strong attention to detail, independent working ability, and comfort adapting to changing guidelines.
• Helpful background: Guideline-based evaluation or quality assurance experience and responsible handling of sensitive information.

How it works

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

About AI training work

AI training is the human work behind artificial intelligence. People review media, assess model outputs, and prepare examples that help AI systems become more accurate and useful; careful reviewers are valued because consistent judgments shape how these systems behave.