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
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
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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