AI INNOVATION CREATIVE CODING
About Me
I'm an AI Engineer who builds the full spectrum of intelligent systems, from deep learning models(PyTorch, TensorFlow) to advanced Generative AI agents (LangChain, LangGraph). I specialize in deploying these solutions as scalable, production-ready services using Docker and FastAPI.
projects
FastChatBot — RAG-Powered LLM Chatbot
An AI-powered chatbot built using Retrieval-Augmented
Generation (RAG) that allows you to query and explore the book "Hands-On Large Language Models" by Jay Alammar.
Combines semantic search with Pinecone vector store
and generative answers from a state-of-the-art open-source LLM deployed through Groq. Features a modular, reproducible pipeline using
DVC with 5 trackable stages: Document Loader → Text
Splitter → Store Index → RAG Inference → Output Generator.
Built with Flask chat UI for elegant real-time
communication and uses all-MiniLM-L6-v2 (384-dim)
compact embeddings for efficient vector search.
Image Classifier API
Built and deployed a computer vision model that classifies images with 95% accuracy. The model is served via a REST API built with FastAPI and containerized with Docker for scalability.
Sales Forecasting Engine
Designed a time-series forecasting model using LSTMs to predict future sales data for an e-commerce client, improving inventory management and reducing overstock by 25%.
Experience
& Timeline
AI Research Intern
Tech Innovators Inc.
- Developed and fine-tuned transformer models for NLP tasks, improving accuracy by 15%.
- Collaborated with the MLOps team to integrate models into the production pipeline.
Machine Learning Intern
Data Insights Co.
- Assisted in building a customer churn prediction model using Scikit-learn and XGBoost.
- Performed data cleaning and feature engineering on large datasets for model training.
Open Source Contributor
Scikit-learn
- Contributed to the library by fixing bugs and improving documentation for the clustering module.
Problem Solving Profile
LeetCode, GeeksforGeeks
- Solved 500+ problems with a focus on Data Structures, Algorithms, and Dynamic Programming.
- Achieved a top 10% rating in weekly contests, demonstrating strong analytical skills under pressure.
- Consistently practice medium and hard level problems to sharpen algorithmic thinking.