AI & ML Engineer | Exploring the frontier of Generative AI, LLMs, and Intelligent Automation | Turning ideas into human-like machines.
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Professional
ML Engineer
June 12, 2026 – Present
Time-Series-Forecasting
June 2, 2026 – Present
Time-Series-Forecasting — GitHub repository
View ProjectAtlas-RAG-Document-Intelligence
March 12, 2026 – Present
An enterprise-grade Retrieval-Augmented Generation (RAG) system that ingests multi-format documents (PDF, DOCX, CSV, images, PPT, etc.) and enables intelligent question answering using Gemini LLM, FAISS vector search, and MiniLM embeddings with a Streamlit-based conversational interface.
View ProjectAgentic-Smart-Ticket-Booking-Assistance-System
March 11, 2026 – Present
Agentic AI travel booking assistant that understands natural language queries, extracts travel intent using LLMs, dynamically calls flight/train/bus APIs, and recommends optimal routes with reasoning, memory, and ethical safeguards.
View ProjectGenoPredictX
September 12, 2025 – November 15, 2025
🧬 GenoPredictX is an AI-powered genetic variant classifier built using XGBoost and a ColumnTransformer pipeline. It predicts disease phenotypes from genomic data, featuring an interactive UI for gene input, disease insights, and doctor consultation integration.
View ProjectRegalCloud-AI-Solutions-Financial-Workflow-Automation-from-Outlook-to-Dockerized-ML
January 5, 2025 – January 10, 2025
This repository showcases an end-to-end automated solution for financial data processing, analysis, and deployment. Built for Regal Finance Solutions, the project integrates Outlook email automation, Google Cloud Platform (GCP) workflows, Python scripting, Power BI dashboards, machine learning model deployment with Flask & Dockerized application.
View ProjectCRUD-Operations-Using-Streamlit
August 22, 2024 – August 22, 2024
This Streamlit web app demonstrates CRUD operations on a MySQL database, allowing you to easily manage user records. It's a practical example of integrating Python with SQL for database management.
View ProjectSalesfoce-Hospital-Management
August 12, 2024 – August 12, 2024
A custom Salesforce-based Hospital Management System with powerful dashboards and data analysis tools. It provides real-time insights into patient care, appointment scheduling, and inventory management, optimizing healthcare operations and decision-making.
View ProjectOpthalmic-disease-screening
December 3, 2023 – December 3, 2023
ODS utilizes deep learning to analyze eye images for diabetes, cataracts, and glaucoma. It's powered by React.js, leveraging VGG19 and ResNet models on Azure for accurate predictions within the app.
View ProjectThe-Data-Talker
November 29, 2023 – November 29, 2023
"Data Talker: An open-source project using Streamlit and Lang Chain's RAG framework for intuitive, natural language-based data analysis. Explore and converse with your data seamlessly via a user-friendly interface."
View ProjectMachine-Learning-Notes
August 10, 2023 – August 20, 2024
Machine Learning Notes - A comprehensive repository featuring my handwritten notes and code files on machine learning. Explore topics like supervised and unsupervised learning, deep learning, and model evaluation. Perfect for students, professionals, and enthusiasts looking to deepen their understanding.
View ProjectCultural Fit Analysis
The candidate's portfolio showcases a strong interest in cutting-edge AI/ML technologies and a drive for practical application, which aligns well with an innovative and results-oriented culture. The breadth of projects, from medical imaging to financial automation and LLM-based systems, indicates adaptability and a willingness to tackle diverse challenges. However, the lack of team-based projects or professional experience beyond a current 'ML Engineer' role (with no start date) makes it difficult to fully assess cultural fit in a collaborative, enterprise environment.
Soft Skills & Operational Fit
The candidate's project descriptions indicate a proactive and self-driven approach to learning and applying new technologies. The diversity of personal projects suggests an ability to work independently and explore various domains within ML. However, without formal assessment data, specific soft skills like teamwork, stress handling, or communication clarity in a professional setting cannot be objectively evaluated.