data labelling
I have worked with iMerit for the past year as an Image Annotation Specialist, where I gained hands-on experience in preparing high-quality datasets for artificial intelligence and machine learning systems. My role mainly involved image annotation using bounding box techniques to accurately identify, label, and classify various objects in images according to project guidelines and quality standards. During my time at iMerit, I worked on annotating a wide range of objects including volleyballs, traffic lights, utility products, farm equipment, and military/war tools, among many others. This required a strong eye for detail, consistency, and precision to ensure every object was correctly outlined and categorized. I handled complex image datasets containing multiple objects, overlapping items, and different environmental conditions such as poor lighting, crowded scenes, and varying camera angles. I developed strong skills in using professional annotation tools to draw accurate bounding boxes, maintain labeling consistency, and meet daily production targets. I also conducted quality checks, reviewed completed tasks, corrected errors, and followed strict client instructions to maintain high annotation accuracy. My experience helped improve my speed, concentration, teamwork, and ability to adapt quickly to new project requirements. Through this role, I built a solid foundation in computer vision data preparation and became highly skilled in supporting AI model training through reliable and precise image annotation services.