I am a Python Developer
Passionate about Python development, machine learning, AI engineering, data analytics, cloud deployments, and backend development on AWS. Let's create something unique!
May 2025 – Present | Remote (Dubai, UAE)
Converted product requirements into technical designs and developed end-to-end React applications integrated with REST APIs and AI modules. Worked on unit and integration testing to ensure high code quality, participated in Agile workflows, and mentored junior developers in React, API integration, and testing best practices.
Techstack: React, JavaScript, Python, REST APIs, AI Modules, GitHub
Jan 2024 – Jul 2024 | Chennai, India
Focused on Python backend development, Power BI, and LLM integrations for a US-based client project. Improved skills in data analysis, AI model integration, and collaborating with client-side teams.
Techstack: Python, Power BI, LLMs, Data Analytics
Jun 2023 – Aug 2023 | Chennai, India
Developed an image-processing API using FastAPI and integrated GAN-based enhancements. Deployed and managed the API on an Ubuntu AWS EC2 instance, strengthening knowledge of cloud computing and advanced image processing pipelines.
Techstack: Python, FastAPI, GAN, AWS, Ubuntu
I architect and build reliable, production-ready REST APIs using Python, FastAPI, and Flask — ideal for SaaS products, dashboards, automation tools, and internal platforms.
I turn raw data into decisions with clean pipelines, analysis, and dashboards using Python, Pandas, and Power BI — so your team sees what actually matters.
I help you ship AI: from classical ML models to LLM-based features like smart search, recommendations, and predictions that plug directly into your product.
I take projects from “works on my machine” to live on AWS with EC2, S3, Docker, and CI/CD — focusing on stability, observability, and clean deployment workflows.
Not sure where to start? I help students, solo devs, and teams refine ideas, choose tech stacks, break down features, and design realistic execution plans.
I create mixed content — code, tech, and day-in-the-life — to make learning more human and less intimidating. I can also help explain complex topics in simple ways for your audience.
Have a project, idea, or feature in mind?
Let’s work together
A CLI-based Python tool that scans your project to auto-generate a clean
requirements.txt, optionally pin versions, format your code
(Black, isort, autopep8), and build Markdown docs from docstrings.
Techstack: Python, Click, Black, isort, autopep8
A standalone Python CLI application to manage doctor & patient records, billing, inventory, and prescriptions, enhanced with AI features to forecast top-used drugs and detect underbilled entries.
Techstack: Python, SQLite3, Pytest, Faker
A web platform that promotes eco-friendly products and community eco-actions, with user login, product uploads, and AI-powered image classification to categorize items as organic or recycled.
Techstack: Flask, MongoDB, TensorFlow, HTML, CSS
Ground station software for the CanSat 2025 competition (TEAM: Dr.MGR-ACS SAT, ID: 2024-ASI-CANSAT-062). The app decodes real-time telemetry and plots key flight metrics from a Can-shaped satellite.
Displays altitude, temperature, airspeed, voltage, pressure, and particle concentration. The demo runs on dummy data; the real system connects to live sensors.
Techstack: Web frontend, real-time plotting, telemetry decoding
Dr. MGR Educational and Research Institute
2021 – 2025
GCPA: 8.84
Specialized in Artificial Intelligence & Data Science. Built strong foundations in algorithms, machine learning, Python, backend development, and cloud deployment. Worked on several practical projects including EcoShop (AI-enabled platform) and VetAI.
Sowdambikaa Matric Boys Higher Secondary School
2019 – 2021
Completed HSC with a strong foundation in Biology and Mathematics, sharpening analytical and reasoning skills.
Sowdambikaa Matric Boys Higher Secondary School
2017 – 2019
Built strong fundamentals across core subjects and developed discipline, consistency, and early interest in technology.
Published in: Journal of Emerging Technology and Innovative Research (JETIR)
Year: 2025
Published a comparative study evaluating machine learning models such as Random Forest, XGBoost, and Logistic Regression for predicting cardiovascular disease, analyzing performance metrics and key medical indicators.
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Issued by Google
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Issued by IBM
Issued by IBM
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Issued by IBM
Issued by IBM
Issued by IBM
Issued by IBM
Issued by IBM
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Issued by IBM
Issued by IBM
Issued by IBM
Issued by IBM
Issued by IBM
Issued by IBM
Issued by Guvi
Issued by IBM
Issued by HackerRank
Issued by HackerRank
Issued by Google
Issued by IBM