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Role
Job Description
This role is responsible for managing the foundational categorization and labeling structures for video AI. You will ensure the taxonomy for video metadata evolves to meet current product use cases and supports a self-sufficient, high-quality data team.
Responsibilities
Maintain and evolve the categorization systems for video metadata, ensuring terms and structures are accurate and scalable.
Execute detailed labeling for AI models, including identifying moving objects or sensor-based video data.
Leverage external annotation and labeling platforms (e.g., Labelbox) and crowdsourced services (e.g., AWS Mechanical Turk) to scale training data efforts.
Cleanse, validate, and organize vast amounts of raw data to ensure it is free from inconsistencies before it feeds into AI models.
Examine data for quality gaps and develop strategies to improve accuracy and categorization value
Qualifications
2–5 years of experience in relevant areas
Experience with taxonomies, library science, archival organization, or music/media store categorization.
Familiarity with data labeling tools (Labelbox) or gig-economy annotation services (Mechanical Turk).
A natural tendency to willingly organize content with a high degree of meticulousness.
Expertise in the full lifecycle of AI training data, from initial sou
📌 Senior Data Quaity support II(Taxonomy (Mumbai)
🏢 Nielsen
📍 Mumbai
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