AI/ML Engineer building scalable intelligent systems—from deep learning models to production-ready GenAI applications.

Languages & Core

Machine Learning & Deep Learning

Generative AI & NLP

DevOps, UI & Databases

• Agentic Workflows: Developing multi-agent systems using LangChain and Mistral for autonomous research and sales automation.
• RAG Architectures: Specialized in Retrieval-Augmented Generation for private document intelligence using Faiss and ChromaDB.
• Computer Vision: Advanced CNN implementations for high-precision image classification and object detection.
• Scalable Deployment: Containerizing AI models with Docker and deploying interactive dashboards with Streamlit.
• Machine Learning: Designing end-to-end ML pipelines—from data preprocessing and feature engineering to model training, evaluation, and deployment.
• Deep Learning & Computer Vision Building CNN-based architectures for image classification, object detection, and real-world vision applications.
• MLOps & Model Lifecycle Experiment tracking, versioning, and reproducible pipelines using MLflow, DVC, and modern deployment practices.
• Scalable AI Deployment Containerizing and serving ML models via FastAPI, Docker, and interactive dashboards for real-world usability.

*   Agentic AI Scholarship App: A FastAPI-based scholarship search and application management system powered by OpenAI, Elasticsearch, and LangGraph.

*   AI Weather Forecasting Tool: An intelligent weather forecasting tool designed to clean and prepare real-world weather data. It predicts temperature, understands natural language queries, and provides users with up-to-date weather information.

*   Detection Of Road Lane OpenCV: This computer vision project detects road lane lines from a dashcam driving video using traditional image processing techniques in OpenCV. It simulates a basic lane-following system, which is an essential component of autonomous driving.