Shaheem Taj Shaik

AI Systems & Software Engineering | VNR VJIET '27

Hyderabad, India

shaheemshaik321@gmail.com

About

I'm a CSE-AIML student at VNR VJIET, graduating in 2027, focused on AI systems and software engineering. My work spans retrieval-augmented generation (RAG), information retrieval, machine learning pipelines, and backend systems. During my ML internship at MapmyGenome, I worked with 500K+ genomic records, developing data-processing and feature-engineering workflows across multiple target variables. I'm interested in the engineering behind AI applications, particularly model evaluation, retrieval quality, reproducibility, and reliable backend infrastructure.

Skills

Python

React

PostgreSQL

Gemini

TensorFlow

PyTorch

Java

Google Cloud

Firebase

Machine Learning

Artificial Intelligence

RAG

LLMs

NLP

Information Retrieval

FastAPI

Docker

TypeScript

Experience

Machine Learning Intern

MapmyGenome

Feb 2026 to May 2026

Built reusable R and SQL pipelines over 500K+ records: ingestion, preprocessing, and feature engineering.
Built modular workflows for four target variables so analyses could be rerun reproducibly.
Turned research requirements into production-oriented data-processing components.

Projects

Tannie - Voice-First AI Study Tutor

A voice-first AI tutor for PDF study sessions that combines real-time voice interaction, page-aware retrieval, and interactive document annotations. Supports document search, study notes, and a browser extension for studying alongside PDFs.

TypeScript

React

Python

FastAPI

Gemini Live API

RAG

PyMuPDF

AI Search Engine

A semantic search and answer-generation system that retrieves relevant information from documents and URLs to generate evidence-grounded responses. Includes relevance ranking, answer-quality evaluation, and A/B benchmarking to assess retrieval performance and hallucination rates.

Python

FastAPI

ChromaDB

Transformer Embeddings

RAG

AI-Powered Learning System

A personalized learning platform that converts uploaded syllabi into structured topics and generates adaptive study schedules based on topic priorities and learning progress. Integrates LLM-guided topic prioritization, deterministic schedule generation, and RAG-based question answering over study materials. My contributions include backend development, adaptive scheduling, and frontend modifications.

Python

FastAPI

React

SQLAlchemy

Ollama

RAG

SQLite

PostgreSQL

Education

B.Tech in Computer Science and Engineering (Artificial Intelligence & Machine Learning)

VNR VJIET

Sept 2023 to Jun 2027