Available for new projects

AI Engineerbuilding thingsthat learn.

I build and ship AI systems that run in production: internal RAG systems, fine-tuned Arabic LLMs, and multi-modal edge inference for human–robot interaction.

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1.5s

RAG time-to-first-token

443

tok/s via vLLM

97%

face-recognition accuracy

70%

workflow time cut

Selected work

Projects

1.5s TTFT

Internal RAG Chatbot

Internal knowledge chatbot on AWS ECS Fargate with an EFS-backed vector store. 1.5s TTFT, 99.9% uptime, plus dashboards tracking query latency and token usage.

ChromaDBLangChainFastAPIAWS ECS

443 tok/s

Arabic News LLM Fine-Tuning

Fine-tuned Qwen2-1.5B with LoRA for Arabic news summarization and entity extraction, then served it with vLLM at 443 tokens/second.

Qwen2LoRAvLLMArabic NLP

7s latency

Human–Robot Interaction (Edge)

Ran SmolVLM2 video inference on Jetson Nano / Raspberry Pi at 7s end-to-end latency for a live VLM + TTS + ASR + LLM system.

SmolVLM2Jetson NanoEdge AIMulti-modal

97% accuracy

AI People Tracking

Led a 9-person team on a mall surveillance system; built the Siamese-network face-recognition module at 97% accuracy to help locate lost children.

Siamese NetFace RecognitionTeam Lead

Arabic Sign Language Classifier

Transfer-learning classifier (ResNet50V2) for the Arabic sign-language alphabet, with a data-augmentation pipeline to handle class imbalance on limited data.

ResNet50V2Transfer LearningAccessibility

TimeMe Chrome Extension

Per-tab time-tracking Chrome extension with productivity analytics. A shipped end-user product, built front to back.

JavaScriptTailwindProduct

Where I've worked

Experience

AI Engineer & Instructor

Saudi Specialized Training & Learning Institute (SSTLI)

Mar 2025 — Present

Dammam, Saudi Arabia

Shipped an internal RAG chatbot (ChromaDB + LangChain + FastAPI) on AWS ECS Fargate — 1.5s TTFT, 99.9% uptime.
Built dashboards tracking query latency, token usage, and sales KPIs in real time.
Optimized SmolVLM2 edge inference on Jetson Nano / Raspberry Pi to 7s for a live human–robot system.
Automated manual workflows with Selenium, cutting task time by 70%.
Taught AI courses to diploma students and business professionals — explaining transformers and vector DBs in plain language.

sr

Upwork (Freelance)

Jul 2024 — Present

Remote

Built and shipped ML solutions for international clients across NLP, computer vision, and data science.
Scoped, built, and deployed working systems independently.

ML Engineer Intern

Digital Egypt Pioneers Initiative (DEPI) — Microsoft Partner

Oct 2024 — Mar 2025

Cairo, Egypt

Built an AI-powered predictive-maintenance pipeline on the NASA bearing dataset, tracked with MLflow and deployed on Azure.
Completed a 6-month program in ML/DL, NLP, CV, Transformers, Generative AI, and Azure.

Toolkit

Skills & Stack

AI / LLMs

PyTorch
Transformers
LoRA Fine-tuning
RAG
LangChain
AI Agents

Product Eng

Python
FastAPI
Flask
Pydantic
REST APIs
n8n

MLOps & Infra

Docker
CI/CD
MLflow
vLLM
llama.cpp
Triton
CUDA

Cloud & Edge

AWS (ECS/EFS/Bedrock)
Azure
GCP
Jetson Nano
Raspberry Pi

Background

About me

I'm an AI Engineer focused on systems that ship and run in production — RAG systems, AI agents, fine-tuned Arabic LLMs, and multi-modal edge inference.

Teaching AI courses keeps me in daily contact with students, instructors, and admins, so I'm used to explainingtransformers, vector databases, and quantization to non-technical people quickly.

I work with Claude Code and Cursor to move from problem to spec to working prototype fast. Fluent in Arabic and English (C2), AWS AI Practitioner certified.

B.Sc. Electronics & Communications Eng.Valid SCE Registration (IT/Telecommunications)AWS Certified AI PractitionerML Specialization — Stanford / DeepLearning.AICS50x — Harvard

Currently

Based in Dammam, Saudi Arabia

Find me

Let's talk

Let's build something
intelligent.

Have a model to train, a pipeline to ship, or an idea worth prototyping? I'd love to hear about it.

ebrahem.hesham.ahmed@gmail.com