Imerit Scholars
The project involved data annotation and labeling tasks used to train and improve machine learning models. I worked on annotating text and image data, including classification, tagging, entity labeling, and relevance assessment based on detailed project guidelines. The project size ranged from hundreds to thousands of data points per batch, with strict turnaround times. Quality was ensured through guideline adherence, consistency checks, self-review, and accuracy benchmarks, with feedback loops used to maintain high annotation precision