Data labelling
This project involved annotating and reviewing multimodal datasets (image, text, and audio) to train machine learning models. Tasks included image bounding boxes, text classification, sentiment analysis, transcription, and data validation. The project handled thousands of samples weekly within structured labeling platforms. Quality was maintained through strict guideline adherence, peer reviews, QA audits, inter-annotator agreement checks, and performance tracking to ensure high accuracy and consistency.