SHIJASMON H

Full-Stack Developer

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About

I'm Shijasmon H, a passionate software engineer currently working as an Assistant Systems Engineer at Tata Consultancy Services (TCS), Mumbai. I specialize in Full Stack Web Development, Artificial Intelligence, and Machine Learning, and have hands-on experience in building scalable, secure, and efficient digital solutions.

With a strong foundation in both frontend and backend technologies, I’ve developed and deployed several full-stack applications using tools like Node.js, Flask, Django, and MongoDB. Technically skilled in Python, JavaScript, SQL, and various frameworks, I’m equally comfortable working on user interfaces, server-side logic, and database integration. I follow Agile development practices and write clean, maintainable, and well-tested code.

I’m driven by a continuous desire to learn and innovate, and I thrive in environments that challenge me to push boundaries and build impactful solutions.

Skills

Python

Java

C++

php

.Net

AI/ML

TensorFlow

PyTorch

OpenCV

NumPy

Pandas

Keras

CNN

Django

Flask

HTML

CSS

Bootstrap

Next.js

MongoDB

MySql

Docker

Kubernetes

REST APIs

JavaScript

Node.js

SQL

AWS

Git

Projects

Shop Inventory Web-App

Shop Inventory Web Application The Shop Inventory Web Application is a full-stack web-based solution designed to help retailers and store owners efficiently manage their product inventory. Built using Node.js for the backend and MongoDB as the database, the application provides a seamless interface for performing CRUD (Create, Read, Update, Delete).

Node.js • MongoDB

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Job point Web-App

A dynamic job portal that aggregates listings from multiple sites via web scraping, allows companies to post jobs, placement officers to share campus drives, and students to view and search all job opportunities in one centralized platform.

Python • Flask • MongoDB • Web Scraping • HTML • CSS • JavaScript • Beutifulsoap

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Digit Recognizer

Digit Recognizer is a machine learning application that identifies handwritten digits (0–9) from input images. It uses Convolutional Neural Networks (CNNs) to analyse image patterns and predict the digit with high accuracy. In this project, the model was trained from scratch using labelled datasets and enhanced using NLP techniques (for preprocessing or user interaction parsing).

CNN • NLP • Django • Python • SQLLite

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Get In Touch

I'm always open to discussing new opportunities and interesting projects.

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