AI Data Annotator / Linguistic Evaluator, Appen
As an AI Data Annotator and Linguistic Evaluator at Appen, I annotated and reviewed large volumes of text and speech datasets for NLP model training. I applied linguistic rules and annotation guidelines to ensure consistency and quality of labeled data, contributing to efficient machine learning workflows. My work helped improve both speed and accuracy across multiple high-volume annotation projects. • Achieved an average task accuracy rate of 98% across assigned projects. • Improved labeling consistency, boosting model training efficiency by 35%. • Completed annotation tasks ahead of deadlines, increasing turnaround speed by 25%. • Utilized specialized annotation platforms for effective dataset review.