I’m a postgraduate from IIT Dhanbad with an M.Tech in Electrical Engineering, specializing in Machine Learning, MLOps, and Quantitative Analysis. My journey has been driven by curiosity, resilience, and a relentless desire to solve challenging problems.
I also took on the UPSC Civil Services, gaining discipline, strategic planning, and mental endurance—even narrowly missing the prelims by 0.17 marks. These lessons now shape how I approach challenges in work and life.
My passion for mathematics naturally evolved into Python programming, Data Science, and Machine Learning. I further refined my skills with a 6-month intensive program at Odin School, applying theory to real-world projects.
Today, I work as a Quantitative Analyst at Opendoor (on payroll of Home.LLC), building production-grade ML systems, collaborating with professionals, and exploring cutting-edge solutions.
Outside of work, I develop personal projects including:
I am passionate about transforming data into actionable insights and building scalable, impactful ML solutions that combine creativity, logic, and technological excellence.
This project is a production-ready, agentic AI system that generates high-quality Medium-style articles using multiple LLM agents, an Editor-in-Chief orchestrator, observability, human-in-the-loop approval, drift detection, Docker, and CI/CD.
Automated ML pipelines with DVC & MLflow. Deployed on Kubernetes with monitoring via Prometheus & Grafana.
Stories GPT RAG is a Retrieval-Augmented Generation (RAG) based AI chatbot that allows users to upload story files (.txt, .pdf, .doc, .docx) or paste text, and ask context-based questions. It is built fully from scratch up to cloud deployment and monitoring.
Built a GPT-2 model from scratch including tokenization, training pipeline, and inference.
A 100% offline, fast, and lightweight fact-checking tool that verifies claims against official Press Information Bureau (PIB) fact-check data.