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Available for Werkstudent / Internship roles

Jainish Parekh

Software Engineer and M.Sc. student in AI for Industrial Applications at OTH Amberg-Weiden. Building full-stack SaaS platforms, real-time data systems, and applied machine learning solutions — with hands-on experience in React, Node.js, Python, and deep learning.

0
Years experience
0
SaaS products shipped
0
IEEE publication
0
Technologies
{"AI": "M.Sc."}
React.js
Node.js
Python
Full-Stack Engineering AI for Industrial Applications Deep Learning React · Node.js · TypeScript Computer Vision LLM & Prompt Engineering REST API Design Real-time Systems Full-Stack Engineering AI for Industrial Applications Deep Learning React · Node.js · TypeScript Computer Vision LLM & Prompt Engineering REST API Design Real-time Systems

Engineering at the
intersection of software & AI.

I'm a results-driven Software Engineer with over a year of professional experience building and optimising B2B SaaS platforms using React, Node.js, and TypeScript. Currently pursuing my Master's in AI for Industrial Applications at OTH Amberg-Weiden, I bridge the gap between robust full-stack engineering and applied machine learning.

My work spans RESTful API design, real-time data systems, frontend performance optimisation, and engineering leadership — including mentoring and code reviews. On the AI side, I've built pipelines with CNNs, RetinaNet, and MobileNetV2, and have hands-on experience with LLMs and prompt engineering.

I'm particularly interested in enterprise-scale AI applications and real-time data systems. Currently seeking a Werkstudent position to apply my expertise in AI and software engineering to solve real industrial challenges.

// Quick facts
Location Amberg, Germany
Origin India
Focus AI · Full-Stack
Current M.Sc. Student
Languages EN · DE
Status Open to work

Tools of the trade.

/ 01

AI & Machine Learning

Python Computer Vision SQL Dataset Augmentation LLM & Prompt Engineering CNN RetinaNet MobileNetV2
/ 02

Backend & APIs

JavaScript TypeScript Node.js Express.js MongoDB RESTful APIs WebSockets
/ 03

Frontend

React Next.js HTML CSS Redux Tailwind
/ 04

Tools & Practices

Figma Git CI/CD Technical Leadership Code Review Agile / Scrum

Where I've built things.

Aug 2024 — Oct 2025

Software Engineer

Pedalsup LLP · Ahmedabad, India

  • Full-stack SaaS development & scalable architecture using React, TypeScript, Node.js, and WebSockets.
  • Designed REST APIs with security compliance and built real-time data systems.
  • Frontend performance optimisation with Redux state management and lazy-loading strategies.
  • Engineering leadership — code reviews, mentoring, and stakeholder communication.
  • Agile delivery, CI/CD pipelines, and cross-functional collaboration.
Jan 2024 — Jun 2024

Software Engineer

Quicko · Ahmedabad, India

  • Production full-stack development with React, Node.js, and MongoDB — UI components & REST API integrations.
  • NoSQL schema design and query optimisation for financial data endpoints.
  • Cross-stack debugging, maintenance, and application stability improvements.
  • Agile team collaboration — code reviews, coding standards, and requirements-to-code translation.

Selected work.

01
MERN · WebSockets · Payments
Jul 2022 — Jan 2023 Full-Stack

Hotel Management Platform

A full-stack responsive web app with real-time booking, secure payment gateway integration, and WebSocket-based availability updates. Includes a comprehensive admin dashboard for data-driven management decisions.

MongoDB Express React Node.js WebSockets REST API
View on GitHub
02
Python · OpenCV · ML
Mar 2022 — Apr 2022 AI / Desktop

Attendance Management System

A Python desktop application automating attendance tracking through real-time face identification using OpenCV and a Random Forest classifier. Async data workflows log entry/exit times into structured CSV reports with high classification accuracy.

Python OpenCV scikit-learn Pandas NumPy Tkinter
View on GitHub
03
React · CSS3 · Responsive UI
Frontend Showcase Frontend

GPT-3 Landing Page

A modern, fully responsive landing page built with React that demonstrates strong frontend development skills through clean component architecture, modular CSS, and thoughtful UI/UX design. Showcases gradient styling, responsive layouts, and reusable React components following modern web development best practices.

React JavaScript CSS3 Responsive Design BEM
Visit Website
04
React · Frontend · UI/UX
Frontend Showcase Frontend

Restaurant Website

An elegant, responsive restaurant website built with React, featuring modern design patterns, smooth scroll animations, and an intuitive user interface. The project highlights strong frontend development capabilities with a focus on visual aesthetics, component reusability, and mobile-first responsive design principles.

React JavaScript CSS3 Responsive Design UI/UX
Visit Website
05
React · FastAPI · Llama-3.2 · TTS
AI · Full-Stack Full-Stack / AI

WeatherFish — AI Weather Assistant

A personalised weather application that generates AI-powered weather summaries using a self-hosted Llama-3.2 model via Ollama on Google Cloud Platform. Users can instantly listen to weather briefings through one-click text-to-speech powered by the Kokoro TTS model. Built with a FastAPI backend and React frontend, the system delivers natural, context-aware weather narratives tailored to the user's location.

React FastAPI Python Ollama Llama-3.2 Kokoro TTS GCP
Visit Website

Academic foundation.

Aug 2020 — May 2024 · EQF Level 6

B.Tech. Computer Science & Engineering

Nirma University · Ahmedabad, India

  • Full-Stack Software Engineering — advanced JavaScript/TypeScript and scalable web architectures.
  • AI & Machine Learning — CNNs, RetinaNet, MobileNetV2, Computer Vision, model benchmarking.
  • Data Science & Backend — MongoDB, SQL, serverless AWS Lambda pipelines.
  • Agile Methodology & Leadership — Scrum, technical team leadership, intern mentoring.

Published research.

IEEE Conference · Co-author & Speaker

Deep Learning Method for Multi-class Face-Mask Classification in Real-Time

IEEE IAICT 2024 Bali, Indonesia Jul 4–6, 2024
85% Multi-class classification accuracy through dataset augmentation
2-Stage Pipeline combining RetinaNet localisation with MobileNet classification
3-Class Detecting correctly worn, missing, and incorrectly worn masks
View repository
// Let's build something

Have an idea?
Let's talk.

I'm currently open to Werkstudent and internship opportunities in AI and software engineering. Whether it's a research collaboration, a product to build, or just a hello — my inbox is open.

jainishparekh21@gmail.com