Senior Data Annotator & Quality Assurance Specialist
I led a team of 5 annotators to complete a high-stakes medical imaging project. We performed semantic segmentation on 10,000 surgical video frames, labeling 15 distinct classes including tissues and instruments. Using CVAT and Supervisely, we overcame challenges like occlusions and variable lighting, maintaining a 98% inter-annotator agreement through rigorous QA. The final dataset contributed to a 15% improvement in a real-time surgical AI model