MUNEEB UR REHMAN
000
AI & Machine Learning Engineer
BS Artificial Intelligence graduate from FAST NUCES building voice agents, RAG pipelines and tested, secure backend APIs that solve real-world problems.
BS Artificial Intelligence · FAST NUCES
2022 — 2026
About
I'm an Artificial Intelligence graduate from FAST NUCES, Karachi. My work sits where research meets production: taking models out of notebooks and into systems that real people use.
I've built voice AI agents that book appointments over the phone, RAG pipelines that answer only from retrieved context, and agentic workflows with LangGraph that review their own output. Every API I ship comes with tests, auth and input validation.
As a Teaching Assistant I reviewed and graded student code across Programming Fundamentals, Assembly and Artificial Intelligence, which sharpened how I explain and structure systems.
Skills
Education
Karachi, Pakistan
Bachelor of Science — Artificial Intelligence
Relevant coursework
cert 01
IBM
cert 02
Udemy
community
Member, FAST Karachi Chapter — Assisted with event management
Experience
Jan 2025 — Dec 2025
FAST NUCES
Karachi, Pakistan
May 2025 — Jun 2025
Wellness Innovations
Remote
Projects
Production appointment booking system for a car detailing business, built on a FastAPI backend and PostgreSQL. A phone-based AI agent answers customer questions from uploaded documents through a RAG engine and books, reschedules or cancels appointments, with an admin dashboard for the knowledge base and calendar.
REST API and web dashboard that registers new patients over a phone call. The voice agent collects details through natural conversation, validates every field and stores the records in a database.
Django REST API that returns a US driving route with the cheapest fuel stops along the way for a 500-mile-range vehicle, shown on an interactive Leaflet map.
Final year project supervised by Dr. Muhammad Rafi. Fine-tuned CodeLLaMA 7B with PEFT LoRA to find and repair software bugs, trained on a bug-fix dataset I built for it.
Flask, Prometheus and Grafana dashboard that tracks application health and CI/CD metrics in real time. Includes rate limiting, API key authentication and automated tests that run through GitHub Actions.
Django web application for memberships, admissions and fee collection, with full CRUD, payment tracking, role based access control and a dashboard of weekly, monthly and yearly sales.
Full-stack Flask app that uses LLMs to semantically match resumes to job descriptions. Produces a detailed compatibility report with skill gap analysis, match score, and structured JSON output. Deployed on Vercel.
Fully local RAG chatbot powered by LLaMA 2 + LangChain. Upload any PDF and have a natural language conversation with it — no API keys, no cloud. Uses FAISS vector store and HuggingFace embeddings for semantic retrieval.
Streamlit app combining user-based collaborative filtering (Pearson correlation) and content-based filtering (genre cosine similarity). Fetches live movie posters via OMDB API. Deployed on Streamlit Community Cloud.
Full-stack laptop marketplace built with Django featuring AI-powered product recommendations, smart search, cart management, order tracking, and a complete admin panel for inventory control.
Streamlit app that validates student transcripts against HEC Pakistan CS degree requirements. Auto-categorizes courses, calculates CGPA, checks 7 credit categories, and generates a downloadable PDF transcript.
Streamlit IR system implementing Boolean Retrieval and Proximity Search from scratch over a research abstract corpus. Supports AND/OR/NOT operators, Porter stemming, and pre-built inverted + positional indexes.
Vector Space Model IR system with TF-IDF weighting and cosine similarity for ranked document retrieval. Built from scratch over research abstracts with a pre-built NumPy matrix index and Streamlit UI.
Content-based filtering system for video games using genre overlap, developer matching, and TF-IDF text similarity on game summaries. Features tiered scoring, fuzzy title search, and Precision@K evaluation.
Contact
I'm open to full-time roles, internships and collaborations in AI engineering, applied ML and backend systems. If you have a problem worth solving, I'd like to hear about it.
