I am a Computer Science & Engineering graduate specializing in Artificial Intelligence and Machine Learning at VIT Bhopal.
My focus is turning ML concepts into working software: training and evaluating models, wrapping them in reliable APIs, and deploying them so they solve real problems.
I work comfortably across the stack an AI engineer needs — data handling with Pandas and NumPy, modeling with scikit-learn and PyTorch, and shipping with FastAPI and Docker.
I am actively looking for internship and entry-level AI/ML roles where I can build, measure, and improve real systems.
Problem: Answering questions accurately over a large private document set without hallucinating.
Built: A retrieval-augmented generation service that chunks and embeds documents, retrieves relevant context, and generates grounded answers with source citations.
Problem: Turning a trained tabular model into a reliable, callable prediction endpoint.
Built: An end-to-end pipeline covering data preprocessing, model training and evaluation, and a FastAPI service that serves predictions, containerized with Docker.
Problem: Classifying unstructured data (e.g. images or text) where classical models fall short.
Built: A PyTorch training pipeline with data augmentation, validation tracking, and a reproducible experiment setup for a neural network classifier.
Math, statistics, and Python data tooling — NumPy, Pandas, and clean data workflows.
Supervised and unsupervised models with scikit-learn, feature engineering, and proper evaluation.
Neural networks with PyTorch — training loops, regularization, and experiment tracking.
Working with large language models and retrieval-augmented generation for grounded applications.
Serving models with FastAPI, containerizing with Docker, and shipping reproducible services.
Actively seeking my first internship. This space is reserved for upcoming roles and project work.
B.Tech, Computer Science & Engineering (AI & ML)
Specialization in Artificial Intelligence and Machine Learning.