Data Labeler – Atlas Capture
Annotated and labeled datasets to support AI model training and development. Applied annotation logic to classify errors, define label granularity, and followed strict object/action rules. Ensured accuracy and consistency across large volumes of data, meeting project deadlines. • Built reference guides and decision charts to streamline annotation processes. • Collaborated with remote teams for adaptation to evolving guidelines. • Maintained high annotation accuracy and quality assurance standards. • Improved annotation workflow efficiency through optimized processes.