Video Data Annotator – Remote (Worldwide)
This is a fully remote position, open to candidates based in 55 countries, including United States, United Kingdom, Canada, Germany, India, France, Netherlands, Singapore. Pay: $8–$10/hr Role Title: Video Data Annotator Role Type: Contractor Location: Remote We are engaging Video Data Annotators to contribute expertise and precision to a customer’s project focused on the advancement of artificial intelligence. In this role, you’ll apply your expertise to help train next-generation AI systems. Your work will shape how models learn, reason, and perform through high-quality, real-world input. No prior experience in AI is required — your domain knowledge is what matters. Scope of Work
- Review and annotate short video and audio clips, labeling content accurately based on project-specific guidelines.
- Assess the accuracy and appropriateness of AI-generated descriptions for diverse multimedia content.
- Evaluate content compliance against clear moderation standards, flagging uncertain or inappropriate material with detailed rationale.
- Provide clear, concise written feedback highlighting potential inaccuracies or ambiguities in AI outputs.
- Maintain rigorous attention to detail and consistency in annotation, ensuring data integrity across high volumes of submissions.
- Collaborate remotely with project managers and fellow specialists to clarify guidelines and support process improvements.
- Safeguard all project data, adhering strictly to confidentiality and data protection standards.
Preferred Qualifications
- Demonstrated experience with video and audio annotation, content labeling, or content moderation for digital platforms.
- Strong command of English, with the ability to communicate feedback and findings clearly in written form.
- Excellent attention to visual and audio detail, with a track record of delivering high-accuracy data annotation.
- Experience working independently and adapting quickly to changing project requirements or guidelines.
- Familiarity with guideline-based evaluation and quality assurance practices.
- Proactive approach to identifying process improvements and sharing best practices with remote collaborators.
- Commitment to maintaining data confidentiality and ethical handling of sensitive information.
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