AI · ML · Data Enthusiast
ML Engineer building end-to-end model training and data pipelines across deep learning architectures (GNN, LSTM, UNet, transformers) and LLM/RAG systems. Hands-on with multilingual NLP (Indic-language RAG), open-source tooling (published PyPI package), local LLM serving (vLLM, ONNX Runtime), and large-scale experimentation across 30+Indian cities. Comfortable taking models from prototype to production.
Specialized in building intelligent systems using cutting-edge AI/ML technologies. Proficient in deep learning frameworks, LLM applications, and MLOps practices.
Passionate about implementing advanced RAG techniques, building agentic AI systems, and creating data-driven solutions that solve real-world problems.
A sophisticated PDF question-answering chatbot that implements multiple advanced Retrieval-Augmented Generation (RAG) techniques for improved accuracy and reasoning capabilities.
Breaks complex questions into simpler sub-questions
Uses step-by-step reasoning to answer questions
Builds and queries a knowledge graph of entities and relationships
Automatically chooses the best technique based on question complexity
Built a train search app with AI-powered personalized recommendations for travel planning.
A Python package for cleaning and processing CPCB (Central Pollution Control Board) air quality data for official government and research use.
Machine learning system to classify student performance with end-to-end pipeline and deployment.