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Moderate brand, metro location, and generalist title increase applicant density.
Annotation skills transferable across industries but require CV tool familiarity, so moderate domain sensitivity.
Explicit 1–3 years requirement plus mandatory annotation tool experience creates moderate filtering.
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Create high-quality labeled video and image datasets (bounding boxes, polygons, segmentation masks, object tracking) to support computer vision model training.
Ensure labeling consistency and adherence to defined annotation guidelines, including frame-level video annotation and maintaining temporal consistency.
Collaborate with data science teams to refine annotation standards, conduct quality checks, and flag ambiguous cases to improve dataset quality.
1-3 years of experience in data annotation/labeling, preferably in computer vision projects.
Bachelor’s degree in any relevant technical domain is required.
Hands-on experience with image/video annotation and familiarity with annotation tools such as CVAT, Labelbox, VGG, Supervisely, etc.
Ability to accurately label bounding boxes, polygons, segmentation masks, and object tracking, following structured guidelines with strong attention to detail.
Demonstrated experience working on video annotation workflows including frame-by-frame labeling and interpolation in computer vision contexts.
Comfortable working with large-scale annotation projects and performing data quality assurance/validation.
Operates with a focus on data quality and detail-oriented annotation within structured team processes supporting model development.