Detail-oriented AI Data Annotator and Content Reviewer with hands-on experience supporting image, video, text, and audio datasets for AI training. Experienced in object detection and image annotation using bounding boxes…
Detail-oriented AI Data Annotator and Content Reviewer with hands-on experience supporting image, video, text, and audio datasets for AI training. Experienced in object detection and image annotation using bounding boxes, polygons, polylines, segmentation masks, and keypoints through practical projects completed with CVAT and Label Studio. Skilled in image evaluation, video action annotation, timestamp annotation, quality assurance, dataset validation, fact-checking, and providing concise written explanations for review decisions. Recognised for strong analytical thinking, exceptional attention to visual detail, consistency, and the ability to work independently while adhering to evolving project guidelines and deadlines.
Supervised field data collection teams across multiple sites, ensuring accuracy, completeness, and compliance with project protocols. Reviewed and verified collected data for consistency, completeness, and integrity before submission. Identified and flagged errors, missing entries, and inconsistencies in field records for correction. Maintained structured documentation and prepared detailed reports summarising findings and quality issues. Coordinated team activities and enforced adherence to operational guidelines and data standards.
Evaluated image-based product listings using structured visual judgment, applying detailed project guidelines and quality standards.
Evaluated product attributes including colour family, materials, categories, patterns, and physical characteristics.
Performed product matching and attribute verification to improve dataset consistency and accuracy.
Applied taxonomy classification principles and documented annotation decisions accurately.
Completed calibration tasks with strong adherence to project instructions and review criteria.
Managed workload reliably in a fully remote environment, demonstrating self-direction, time management, and consistent output quality.
Reviewed and labeled hand movements, actions, and interactions in video datasets.
Identified precise timestamps and segmented action sequences according to project specifications.
Maintained annotation consistency and adhered to detailed quality guidelines.
Flagged unclear cases and ensured accurate documentation of annotation decisions.
Evaluated AI-generated responses for accuracy, helpfulness, reasoning quality, and instruction adherence.
Crafted high-quality prompts and responses to test and improve AI model capabilities and documented evaluation findings with a high level of granularity.
Applied annotation guidelines and quality standards to support AI model improvement.
Identified factual inaccuracies, inconsistencies, and content quality issues across multiple task categories.
Contributed human feedback used for AI training and evaluation workflows.
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