Aditya Gautam

I am an AI/ML engineer with hands-on experience building production-oriented ML systems, RAG chatbots, and deep learning models. I deliver privacy-aware, offline solutions and scalable data pipelines that improve latency and QA performance.

During a machine-learning internship at Bharat Electronics Ltd., I built DocSense, an offline RAG chatbot using Ollama, LangChain, and ChromaDB, engineered chunking and embedding pipelines to cut query latency by 30%, and implemented table and image parsers to raise non-text QA accuracy by ~25%.

Outside internships, I developed several projects including a modular quantitative trading system with a full backtesting engine (achieving simulated annual returns of 18–27%), a multi-service AI productivity platform with CI/CD and Docker deployment, and a CNN-based dog-breed classifier that improved validation accuracy from 85% to 93%.

I hold research and competition credentials (IEEE publication, Adobe Hackathon) and a Google Cloud Professional Data Engineer certification. I seek roles where I can apply ML/AI expertise to deliver robust, production-grade systems and continue learning MLOps and scalable ML deployments.