Puedes aplicar desde República Dominicana
Video Annotation Specialist
Worldwide · Remoto8-10 USD Por hora
Resumen de la oportunidad
Video Annotation Specialist en micro1. Es una oportunidad remota. Ubicación publicada: Worldwide. La fuente aporta evidencia de que puede solicitarse desde República Dominicana.
- Empresa
- micro1
- Ubicación
- Worldwide
- Modalidad
- Remoto
- Tipo de contrato
- CONTRACTOR
- Salario publicado
- 8-10 USD Por hora
- Disponibilidad desde República Dominicana
- Puedes aplicar desde República Dominicana
- Actualizada
- 02 de octubre de 2026
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Descripción del empleo
Requisitos
- Demonstrated experience in data annotation, labeling, or content moderation - particularly with video or audio data.
- Strong English communication skills, with the ability to provide detailed written and verbal feedback.
- Keen attention to detail and the ability to apply consistent, objective judgment throughout repetitive tasks.
- Familiarity with generalist training, content review, or guideline-based evaluation is advantageous.
- Comfort working independently and reliably in a remote project setting.
- Adaptability to quickly learn new annotation tools, protocols, and quality standards.
- Commitment to upholding data confidentiality and accuracy throughout the engagement.
- Originally posted on Himalayas
Location: Remote
micro1 is engaging Video Annotation Specialists to support a customer’s AI training project focused on video and audio analysis. 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 short video and audio clips, scrutinizing both visual and auditory elements for detailed annotation and assessment.
- Evaluate the accuracy of AI-generated descriptions, verifying alignment with provided guidelines and identifying inconsistencies or errors.
- Deliver clear, concise written feedback to highlight inaccuracies, ambiguities, or areas of uncertainty in the reviewed content.
- Apply consistent judgment to ensure that content labeling supports robust AI evaluation and training objectives.
- Flag content that does not meet specified standards or requires further clarification from project leads.
- Collaborate with project coordinators and follow project protocols to maintain high annotation quality and data integrity.
- Contribute to continual process improvement by suggesting annotation and quality assurance enhancements.