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Jaideep Kundu

@jaideepkundu

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Computer science student building real-time AI and full-stack systems; seeking backend, full-stack, or ML internships.

India

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What I'm looking for

I’m looking for a summer internship where I can build backend or full-stack features and apply ML for practical, real-time user experiences—owning APIs, scaling services with Docker, and growing fast in a production environment.

I’m a third-year B.Tech CSE student at VIT-AP, and I build real-world applications across backend, full-stack, and AI/ML. I’m especially drawn to systems that feel fast and intelligent—where latency, reliability, and user experience actually matter.

In my projects, I architect AI-powered experiences using Retrieval-Augmented Generation (RAG) and vector search. For DeepContext Engine, I built a RAG platform with Pinecone-based semantic retrieval across 10,000+ document chunks and streaming Flask REST APIs with conversational memory at <300ms average latency.

I also enjoy building collaborative and real-time product features. In CollabDocs, I implemented a real-time collaborative document editor for 20+ concurrent users using operational transformation (OT) algorithms, achieving <50ms update propagation through WebSocket pipelines and Redis Pub/Sub for decoupled, horizontally scalable communication.

On the AI engineering side, I’ve worked on ML systems that prioritize performance and deployment. MedDiagno delivers 87%+ screening accuracy using XGBoost and Gradient Boosting with <2s inference, while LifeTracker integrates a Gemini API for personalized insights—both secured with JWT authentication and deployed with Docker. Outside projects, I’ve led hands-on Computer Vision sessions using OpenCV and MediaPipe, and I like turning concepts into working demos.

Experience

Work history, roles, and key accomplishments

Core Member, Technical Team

Microsoft Students Chapter

Aug 2024 - May 2025 (9 months)

Conducted hands-on technical sessions on Computer Vision using OpenCV and MediaPipe for a cohort of 30+ students, covering real-world applications in gesture recognition and object detection.

OpenCV MediaPipe Computer Vision Object Detection Technical Training Python Real World Application Mediapipe

LifeTracker Full-Stack App

LifeTracker

Built a full-stack productivity and finance tracker with expense monitoring, habit tracking, and analytics dashboards, integrating the Gemini API to generate personalized behavioral and financial insights. Implemented JWT authentication with secure session management and cron-based pipelines for automated recurring aggregation and weekly report generation.

MongoDB Gemini API JWT Full Stack Dashboards REST APIs

CollabDocs Real-Time Editor

CollabDocs

Developed a real-time collaborative document editor supporting 20+ concurrent users using operational transformation (OT) to ensure 100% document consistency across simultaneous edits. Achieved <50ms update propagation via WebSocket pipelines and used Redis Pub/Sub to decouple event broadcasting for horizontal scaling.

WebSockets JavaScript

DeepContext Engine

Architected a RAG platform for context-aware conversational AI with sub-second semantic retrieval across 10,000+ document chunks using Pinecone vector search and embedding models. Built streaming Flask REST APIs with conversational memory, delivering multi-turn interactions at <300ms average latency and reduced deployment setup time by ~60% with Docker.

Python Flask Retrieval Augmented Generation (RAG)Pinecone Vector Search Embeddings Docker REST APIs Semantic Search

MedDiagno AI Diagnostics

MedDiagno

Engineered an AI diagnostics platform for diabetes, heart disease, and skin cancer screening with 87%+ accuracy using XGBoost and Gradient Boosting and <2s end-to-end inference. Implemented JWT-secured authentication, prediction history, and dashboards, persisting 10,000+ records in MongoDB Atlas and deploying as modular Docker services.

Flask MongoDB Atlas XGBoost Gradient Boosting JWT Docker Machine Learning Data & Persistence Dashboards

Education

Degrees, certifications, and relevant coursework

Vellore Institute of Technology, Andhra Pradesh

Bachelor of Technology, Computer Science & Engineering

2023 -

Grade: CGPA: 7.53

Pursuing a B.Tech in Computer Science & Engineering at VIT-AP, with a CGPA of 7.53. Currently in the third year and seeking backend, full-stack, or ML internship opportunities.