AI Data Annotation Specialist Computer Vision and NLP Projects
Worked as an AI Data Annotation Specialist on multiple midscale datasets supporting machine learning model development in healthcare, retail, and chatbot systems. For computer vision tasks, I annotated over 50,000 images using bounding boxes and semantic segmentation techniques to identify objects such as medical equipment, retail products, and human activity patterns. Ensured high precision labeling using tools like CVAT and LabelImg, maintaining strict adherence to annotation guidelines. For NLP projects, I labeled and classified over 30,000 text samples, including customer queries and clinical notes. Tasks included intent classification, sentiment analysis, and Named Entity Recognition (NER) to extract structured information such as names, dates, symptoms, and product references. Maintained a consistent accuracy rate of 97%+ through peer reviews, guideline validation, and iterative feedback loops with QA teams. Actively participated in dataset validation, error correction, and guideline refinement to improve overall dataset quality and model performance.