Data/Video Annotation Specialist
As a Data/Video Annotation Specialist, I annotated thousands of images and video frames using precise bounding boxes, segmentation, and object tracking methods. I followed detailed project guidelines to maintain a high level of annotation accuracy and consistency. I worked closely with quality assurance teams to review and correct any mislabeled data, ensuring robust datasets for machine learning experiments. • Used annotation tools such as Labelbox, CVAT, VGG Image Annotator, Supervisely, and Roboflow. • Labeled datasets included domains such as autonomous driving, retail product labeling, and sports video analytics. • Maintained organized metadata and clear file structures to facilitate ML experiment integration. • Achieved accuracy rates of 97–99% in labeling projects.