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The role involves analyzing video content and accurately tagging, labeling, and annotating people, actions, and events. The annotations will contribute to building high-quality datasets that support AI/ML and computer vision applications.
Job Responsibility:
Watch and analyze video footage frame-by-frame
Accurately annotate people and relevant objects in the video
Identify and tag movements, activities, and interactions
Label specific events according to project guidelines
Ensure consistency, accuracy, and adherence to defined annotation standards
Collaborate with the project team to clarify rules, edge cases, and quality expectations
Meet daily or weekly annotation targets with high accuracy
Perform quality checks on annotated data and make corrections as required
Requirements:
Graduate in any discipline (any specialization accepted)
Prior experience in video annotation, data labeling, or similar projects is an advantage
Freshers with strong observation skills may also apply
Basic computer literacy
Familiarity with annotation tools/software (training will be provided if required)
Strong attention to detail and observational skills
Ability to focus on repetitive tasks without compromising accuracy
Good communication skills and ability to follow structured guidelines
What we offer:
Hands-on exposure to AI/ML and computer vision-based projects
Opportunity to work on varied video annotation assignments
Potential career progression to roles such as Quality Reviewer or Team Lead for annotation teams
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