I develop cloud-native data pipelines, train and serve ML Systems, and build backend & app services.
I'm a 3rd year B.Tech Information Technology student at VIT Vellore, India, focused on Cloud & Data Engineering. I build end-to-end data systems, from ETL ingestion, storage and processing, to model training and real-time inference, with an eye on cost-efficiency, performance and maintainability. I also develop backend services and mobile apps when projects need full-stack delivery.
Core capabilities across cloud & data, ML systems, backend services and Flutter app development.
S3, Athena, Glue, Lambda, SageMaker, Medallion architecture, ETL & query optimization.
Model training & deployment (XGBoost, Scikit-learn, SageMaker, FastAPI), feature engineering.
APIs and production services using Node.js/Express, PostgreSQL, JWT, Docker, and REST best practices.
Flutter apps with Maps integration, storage, and performant UI patterns for Android/iOS.
Designed a medallion ETL with S3 partitioning and Parquet, improved Athena query performance by ~70%, trained XGBoost on SageMaker and deployed real-time inference via FastAPI on EC2 with Docker. Serverless ETL reduced infra costs significantly.
Built the event backend (150+ participants) with Node.js, Express and PostgreSQL. Implemented JWT auth and admin workflows to automate tasks and maintain >99% uptime during the event.
ML pipeline using RDKit Morgan fingerprints on an SGD classifier to predict catalysts; improved recall and reduced physical experiment trials. Employed joblib for fast inference.
Led cross-functional technical projects: coordinated dev & design teams, conducted technical interviews, mentored juniors, and ensured code quality. Drove process improvements and managed financial operations.
Worked on modular Flutter components, performance tuning, and implemented self-check mechanisms to catch regressions early. Participated in code reviews to boost app stability.
