Data Annotator | Outlier
Evaluated AI-generated content for quality, relevance, and accuracy according to task specifications. Labeled text and data to support training and fine-tuning of machine learning models. Maintained strong performance metrics and high task completion rates while providing actionable feedback to improve annotation processes. • Assessed content against relevance and accuracy criteria • Produced labels required for model learning workflows • Monitored throughput and quality to sustain metrics • Supplied feedback to refine future annotation guidelines