AI Data Annotation Specialist – Multi-Modal Dataset Labeling
Worked on video annotation projects for AI and machine learning applications, focusing on accurate frame-by-frame labeling and object tracking. Annotated video datasets by identifying and labeling objects using bounding boxes and polygons, ensuring consistency across frames. Performed object tracking across sequences to support motion detection and behavioral analysis models. Labeled events and actions within videos, including human activities and object interactions, to improve model understanding of temporal patterns. Handled large volumes of video data, including hours of footage, while maintaining high precision and adherence to annotation guidelines. Conducted quality assurance checks to ensure accuracy, consistency, and completeness of labeled data. Collaborated with project teams to refine labeling instructions, improve workflow efficiency, and meet project deadlines. Demonstrated strong attention to detail in complex scenes involving multiple objects and dynamic movement.