Data Labeller & Annotator – Scale AI / Appen / Remotasks
Labeled and annotated large volumes of multimodal data, including sentiment classification, named entity recognition, bounding box annotation, and image captioning. Maintained quality by meeting or exceeding platform accuracy thresholds and contributing clean datasets for production model training pipelines. Performed QA reviews on peer annotations to identify systematic errors and provide corrective feedback for improved batch quality. • Annotated text, image, and audio samples across multiple labeling task schemas. • Conducted quality assurance and corrective peer feedback. • Completed sensitive tasks such as content moderation, toxicity detection, and AI safety evaluation. • Adapted to evolving guidelines with minimal revision cycles.