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Hello, I'm
Vardhan.

Building scalable full-stack applications and deploying them where they belong — the cloud.

A little about me

I'm a software engineer passionate about building products that matter — from web apps to cloud infrastructure and AI systems. I care deeply about developer experience, clean architecture, and the intersection of design and engineering.

When I'm not writing code, you'll find me writing on my blog, exploring new tools, or experimenting with cloud deployments and AI workflows. I believe great software is a craft — and I'm always learning.

Based in India. Open to remote opportunities worldwide.

4+Years of experience
3+Projects shipped
Tabs open

What I work with

Web

  • React
  • JavaScript
  • Node.js
  • Tailwind CSS
  • MongoDB

AI & ML

  • Python
  • LangChain
  • HuggingFace
  • Prompt Engineering

Cloud & DevOps

  • AWS
  • Docker
  • Jenkins
  • Linux

Tools

  • Git
  • Figma
  • Jira
  • Postman

Things I've built

2025

Music Genre Classification

A dual-branch deep learning architecture was designed for music genre classification. The first branch processes raw audio waveforms using 1D convolutional layers to extract temporal features, while the second branch processes Mel-spectrograms using 2D convolutional layers to capture spectral characteristics. The feature vectors from both branches are concatenated and passed through fully connected layers for final genre prediction.

2025

Roadside Assistance System

Built a MERN-stack Roadside Assistance System that automatically detects user location and connects stranded vehicle owners with nearby mechanics. Implemented GPS-based location tracking, real-time request management, authentication, and service status updates using React, Node.js, Express, MongoDB, and Socket.io.

2026

AI-Based PDF Question Answering System (RAG)

Developed an AI-powered PDF Question Answering system using LangChain and Pinecone that enables users to upload PDF documents and retrieve accurate, context-aware answers through semantic search and Retrieval-Augmented Generation (RAG). Implemented PDF text extraction, vector embedding generation, document retrieval, and LLM-based response generation.

Let's work together

Open to new opportunities, collaborations, or just a good conversation. Send me a message and I'll get back to you.

Resume