AI/ML Engineer (Data Labeling & AI Training – NER/Classification)
Text
Entity (NER) ClassificationContributed to data labeling and AI training for entity recognition and classification in biomedical and clinical datasets. Applied fine-tuning and transfer learning on NLP pipelines using frameworks such as PyTorch, TensorFlow, and HuggingFace Transformers. Ensured compliance with regulatory requirements through rigorous model and data validation protocols. • Labeled and classified clinical and health-related texts for entity extraction and categorization. • Engaged in model fine-tuning for named entity recognition and text classification tasks using annotated data. • Used Python-based ML tools and internal/proprietary software for annotating large-scale biomedical datasets. • Supported pipeline evaluation and iterative improvements based on annotation accuracy and feedback.