Remote Content Review and Data Annotation Support
Evaluated digital content and datasets as part of projects aimed at improving AI training data quality. Reviewed AI-generated responses, selecting outputs based on clarity, accuracy, and factual correctness. Conducted structured quality checks to maintain annotation consistency and dataset reliability. • Labeled and categorized text, image, and multimedia data for machine learning training. • Applied detailed rubrics to evaluate and rate AI outputs systematically. • Delivered feedback for continuous improvement of labeling guidelines. • Supported AI product teams with reliable annotated data.