AI Data & LLM Training Contributor
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ClassificationWorked on AI data annotation and LLM training datasets across multiple domains including healthcare, NLP, and e-commerce. Responsibilities included labeling and classifying large-scale text datasets, performing named entity recognition (NER) on structured and unstructured medical and general text, and evaluating sentiment and intent in conversational data for chatbot and LLM training. Also contributed to search relevance evaluation by rating and comparing search results based on user intent and contextual accuracy. Ensured high-quality annotations by strictly following project guidelines, maintaining consistency, and performing self-review to minimize errors. Worked with mixed data types including text, structured records, and image-based product data to support AI model training pipelines. Focused on accuracy, consistency, and adherence to QA standards to improve dataset reliability for machine learning models.