Machine Learning & Agentic AI

Mohanad
Yehia

I ship models, not just notebooks.

AI engineer working the full lifecycle — from scraping raw data and fine-tuning LLMs to deploying on the edge and wrapping it all in a production backend.

live activation map
01 — About

The part most demos skip.

Getting a model out of the notebook and into something people can actually use.

I work across the whole machine-learning lifecycle — from cleaning messy, scraped data to fine-tuning language models and running them on constrained edge hardware like the Jetson Nano.

Lately I’ve been building agentic and RAG systems: I fine-tuned Qwen 1.5B on a hand-curated dataset so it answers domain questions in a specific voice, and I stand these models up behind FastAPI backends with scraping and browser automation feeding them real data.

I also teach — I like breaking hard AI concepts down until they click, which keeps my own fundamentals sharp.

97%
face-recognition accuracy // grad project
0.999
fraud-detection test accuracy
1.6M
tweets processed // NLP
1.5B
params fine-tuned // Qwen
02 — Stack

Tools I actually reach for.

Grouped by where they show up in the pipeline.

03 — Selected work

Things I built.

From LLM fine-tuning to computer vision — a mix of shipped systems and deep-dive experiments.

04 — Certificates

Where I kept learning.

Open to work

Let’s build something
that ships.

Got a model to fine-tune, a RAG system to stand up, or an idea that needs to leave the notebook? I’m based in Dammam and happy to talk.