Alebel Melak

I’m an AI Data Labeler focused on computer vision data annotation, where I build reliable ground-truth datasets that teams can trust. I annotate image datasets using CVAT while following detailed project guidelines and labeling standards.

In my current role at iCog Labs, I create consistent object annotations across large datasets. I also review and validate annotations to ensure quality, completeness, and compliance—identifying errors early, correcting them before submission, and documenting ambiguous cases instead of making assumptions.

Previously, as a Data Entry Volunteer, I processed and validated over 250 records daily with 99.5% accuracy. I performed data quality checks, resolved inconsistencies, and reviewed duplicate, incomplete, and inaccurate records to prepare clean, structured datasets for reporting and analysis.

My Biomedical Engineering background supports my analytical thinking and meticulous inspection. I’m committed to producing high-quality training data, communicating clearly in English, and working confidently in Amharic.