Machine Learning Engineer and Information Technology student @ Al-Quds University (Dual Studies Program), blending academics with hands-on industry experience in software engineering, data pipelines, and applied AI. Focused on solving real-world problems through retrieval, ranking, and recommendation systems.
- Languages & Frameworks: Python, Java, Kotlin, Flask, FastAPI, Airflow, Docker
- AI & Data: Pandas, Polars, NumPy, Scikit-learn, PyTorch, TensorFlow, SBERT, Qdrant, Elasticsearch
- Full-Stack: Java, Firebase, REST APIs, GitHub CI/CD
- Concepts: ML engineering, retrieval & ranking, data pipelines, NLP, CV, backend development
-
Machine Learning Engineer Intern @ DevelopOn Improved retrieval accuracy for a production AI agent handling documents across many client projects/apartments; architecting ATS-ML-API, an ML platform for an Applicant Tracking System spanning retrieval, ranking, and recommendation services.
-
Software Engineer Intern @ Sada Intelligent Solutions (Past) Built a spec-driven Android finance app (Cashbook) using Kotlin + Firebase, leveraging LLMs for development automation.
-
Python Developer Intern @ ProGineer / PDF Solutions (Past) Built Polars-based wafer data pipelines and Flask-Airflow plugins; simulated die-cutting and batching processes in Python.
| Project | TL;DR |
|---|---|
| WardrobeGenie | End-to-end AI fashion recommendation system combining computer vision, semantic vector search, neural outfit ranking, and adaptive personalization with FastAPI, PyTorch, Qdrant, Docker, and Apache Airflow. |
| Radar-Based Human Detection (IOAI 2025) | U-Net semantic segmentation on radar heatmaps — 0.957 private leaderboard score |
| Chameleon AI Word Guesser (IOAI 2025) | SBERT-based ensemble inference — 89%+ leaderboard score |
| Recipe Recommender System | TF-IDF + Flask search engine over 2M+ recipes |
| Dog Breed Vision | CNN Transfer Learning model trained across 120 dog breeds |
3D printing, Kaggle competitions, MLOps, AgenticAI.