Build end-to-end systems integrating structured and unstructured data stores, graph databases, indexing strategies, and reinforced learning strategies, embedding models, and LLMs to enable context-aware, knowledge-grounded responses. Design, train, and deploy end-to-end machine learning pipelines encompassing data ingestion, feature engineering, model selection, hyperparameter tuning, and validation using frameworks such as scikit-learn, XGBoost, PyTorch, and TensorFlow.