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AI Summary
The role involves annotating and reviewing videos and images to identify specific features for AI models focused on child anthropometry. Responsibilities include evaluating video quality against predefined criteria and validating movement trajectories.
- Support critical data annotation tasks for AI models aimed
at improving healthcare outcomes, specifically in child
anthropometry and growth monitoring.
- Review videos and/or images and annotate specific features related to:
- Video quality
- Video content
- Identification and marking of different objects within videos/images
- Video quality
- Evaluate videos against predefined quality criteria to determine validity, including:
- Video errors and quality issues
- Child/baby-related concerns
- Lighting and shadow issues
- Presence of other individuals in the frame
- Problems with reference objects
- Errors in capturing the movement trajectory or arc
- Video errors and quality issues
- Perform additional annotation or validation tasks as
required by the project.
Requirements
Educational Qualification
- Bachelor’s degree in any relevant discipline from a
recognized university.
- Candidates with backgrounds in life sciences, computer
science, healthcare, or related fields will be preferred.
Experience
Essential:
- 0–3 years of experience in image/video annotation, quality
review, or data labelling projects.
- Familiarity with annotation tools and attention to detail in
reviewing visual data.
Preferred Skills
- Good observation skills and ability to identify
errors/inconsistencies in images and videos.
- Strong communication and interpersonal skills.
- Prior exposure to AI/ML or healthcare-related projects,
particularly child health, anthropometry, or growth monitoring,
is an advantage.
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