Ninad
Belorkar

Software Intern

Computer Science Engineer

Ninad Belorkar

Learning technology. Building solutions. Growing as an engineer.

Experience

Software Intern — ifm

Working on software engineering and testing at ifm, contributing to internal tooling, quality assurance workflows, and backend systems. Gaining hands-on experience in professional software development practices.

Software Engineering · Testing · Cloud

ProjectsAll projects →
AI-Integrated Test Case Management System poster

AI-Integrated Test Case Management System

An AI-powered platform for automated test case generation and management, built as part of the Silicon Stack industry project.

Problem

Manual test case creation is time-consuming, inconsistent, and difficult to scale across large codebases. Teams spend significant effort writing boilerplate test cases that could be systematically generated.

Built

A full-stack web application that integrates with the Gemini API to automatically generate structured test cases from user requirements. The platform provides a management interface for organising, reviewing, and exporting generated test cases.

Engineering

Built with a React/Next.js frontend and a Flask/Python backend. The AI pipeline processes requirement descriptions through Gemini API to produce structured test cases with preconditions, steps, and expected outcomes. Test case data is persisted in PostgreSQL with a Prisma ORM layer.

React · Next.js · TypeScript · Python · Flask · Gemini API · PostgreSQL · Prisma · REST APIs

VideoVault poster

VideoVault

An intelligent video data-hiding service that embeds and extracts hidden data within video files using cloud-native infrastructure.

Problem

Securely transmitting hidden information within video content requires combining steganography algorithms with reliable, scalable cloud infrastructure — a non-trivial engineering challenge.

Built

A cloud-native service that accepts video uploads, processes them through an OpenCV-based steganography pipeline to embed or extract hidden data, and returns the processed output. The entire service is containerised and deployed on AWS Fargate.

Engineering

The processing pipeline is built in Python using OpenCV for frame-level steganography. Docker containers are pushed to AWS ECR and orchestrated via AWS Fargate for serverless execution. Infrastructure is provisioned with Terraform. The deployment pipeline is automated through GitHub Actions.

Python · OpenCV · AWS · Docker · Terraform · AWS Fargate · ECR · GitHub Actions

Skills

Programming Languages

C# · C · C++ · Python

Cloud & DevOps

AWS (EC2, S3, Lambda, API Gateway, Fargate, SNS, IAM) · Docker · Terraform · Infrastructure as Code · Ansible · Linux · Bash · Git · GitHub · CI/CD Basics

Databases

SQL · MongoDB · Amazon RDS · DynamoDB

Mobile & Web Development

Flutter · Dart · Android Studio · HTML · CSS

Software Testing

Test Case Design · SDLC/STLC · Exploratory Testing · Automated Testing · Playwright Basics · Jira · API Testing Fundamentals

Machine Learning

scikit-learn · Data Cleaning · Preprocessing · Visualization

About

I build things, understand the engineering behind them, and I'm growing into a strong software engineer.

My background spans backend systems, cloud infrastructure, AI integration, and software testing — areas I've explored through internships and personal projects.

I care about understanding the engineering behind what I build, not just getting something to work. I'm early in my career, actively learning, and looking for opportunities to contribute to meaningful work.

Currently

Software Intern at ifm

Exploring software engineering, testing, cloud technologies & AI.

Contact

Have an opportunity
or want to connect?

I'm always open to conversations about software engineering, technology and opportunities.