Saunak Das Chaudhuri

WORK HISTORY

EDUCATION

ABOUT SAUNAK DAS CHAUDHURI

I am an AI/ML Engineer and Data Scientist with hands-on experience designing and shipping end-to-end, production-grade AI systems—from data ingestion and experimentation to ML/LLM deployment. My work focuses on building scalable, explainable, and business-impactful AI products, particularly in GenAI, Retrieval-Augmented Generation (RAG), causal inference, and multimodal learning.Currently pursuing a B.Tech in Electronics & Communication Engineering at BIT Mesra, I bridge strong engineering fundamentals with applied machine learning and modern AI system design. I have worked on both research-driven and product-oriented problems, translating complex models into reliable, deployable solutions.What I do best:LLM & GenAI Systems: Designed RAG pipelines using FAISS, LangChain, and Hugging Face to reduce hallucinations and improve response grounding and reliability.Data & ML Infrastructure: Built a high-performance custom PyPI package for large-scale data ingestion, transformation, caching, and retrieval—achieving 35–40% latency reduction on million-row datasets.Causal Inference & Experimentation: Applied A/B testing, Difference-in-Differences, and Propensity Score Matching to move beyond correlation and quantify true product impact.Research & Applied ML: Conducted comparative research on GNNs vs ANNs for biochemical optimization, achieving ~20% accuracy improvement through relational modeling.Multimodal AI: Developed vision-language systems combining CNNs and transformers for context-aware understanding.Technical strengths:Languages & Tools: Python, SQL, PyTorch, TensorFlow, Hugging Face, LangChain, FAISS, Scikit-learn, XGBoost, OpenCVAI/ML: LLM systems (RAG), NLP, Deep Learning, Computer Vision, Multimodal Learning, Explainable AI (SHAP)Data & MLOps: ETL/ELT pipelines, Airflow, Spark, Kafka, FastAPI, Docker, Vector DatabasesAnalytics: Causal Inference, A/B Testing, Product Analytics, Statistical ModelingI have been recognized as a Hackademia 2025 Finalist, BIT Mesra Best ML Project Winner (2024), and Kaggle Expert, and I enjoy working in fast-paced environments where AI systems are expected to move real business metrics, not just benchmarks.I am actively interested in AI/ML Engineer, GenAI Engineer, and Data Scientist roles where I can contribute to building defensible, scalable AI-powered products at the intersection of engineering, research, and product impact.