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I am a motivated and results-driven AI Engineer with hands-on experience in developing, deploying, and optimizing end-to-end machine learning and deep learning solutions. I specialize in computer vision tasks such as object detection, pose estimation, segmentation, and OCR, as well as generative AI including RAG, LLM agents, and GANs. I have built and deployed real-world applications using cutting-edge technologies such as YOLOv8, EasyOCR, MediaPipe, and StrongSORT, including license plate recognition systems, virtual mouse control, and PPE compliance for construction sites. With proficiency in designing and fine-tuning models using PyTorch, TensorFlow, and OpenCV, I focus strongly on performance and accuracy. I am experienced in developing generative AI applications with LangChain, LangGraph, and LlamaIndex, including PDF-based Q&A bots, smart assistants, and self-reviewing email writers. I am skilled with cloud deployment, Streamlit, Docker, and scalable data pipelines, and excel at collaborating in agile teams to continuously improve models through active learning, data annotation, and evaluation.…I am a motivated and results-driven AI Engineer with hands-on experience in developing, deploying, and optimizing end-to-end machine learning and deep learning solutions. I specialize in computer vision tasks such as object detection, pose estimation, segmentation, and OCR, as well as generative AI including RAG, LLM agents, and GANs. I have built and deployed real-world applications using cutting-edge technologies such as YOLOv8, EasyOCR, MediaPipe, and StrongSORT, including license plate recognition systems, virtual mouse control, and PPE compliance for construction sites. With proficiency in designing and fine-tuning models using PyTorch, TensorFlow, and OpenCV, I focus strongly on performance and accuracy. I am experienced in developing generative AI applications with LangChain, LangGraph, and LlamaIndex, including PDF-based Q&A bots, smart assistants, and self-reviewing email writers. I am skilled with cloud deployment, Streamlit, Docker, and scalable data pipelines, and excel at collaborating in agile teams to continuously improve models through active learning, data annotation, and evaluation.

Ahmed Magdy Ghida

AI Engineer, Developer, Data Scientist, +4

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I am a motivated and results-driven AI Engineer with hands-on experience in developing, deploying, and optimizing end-to-end machine learning and deep learning solutions. I specialize in computer vision tasks such as object detection, pose estimation, segmentation, and OCR, as well as generative AI including RAG, LLM agents, and GANs. I have built and deployed real-world applications using cutting-edge technologies such as YOLOv8, EasyOCR, MediaPipe, and StrongSORT, including license plate recognition systems, virtual mouse control, and PPE compliance for construction sites. With proficiency in designing and fine-tuning models using PyTorch, TensorFlow, and OpenCV, I focus strongly on performance and accuracy. I am experienced in developing generative AI applications with LangChain, LangGraph, and LlamaIndex, including PDF-based Q&A bots, smart assistants, and self-reviewing email writers. I am skilled with cloud deployment, Streamlit, Docker, and scalable data pipelines, and excel at collaborating in agile teams to continuously improve models through active learning, data annotation, and evaluation.…I am a motivated and results-driven AI Engineer with hands-on experience in developing, deploying, and optimizing end-to-end machine learning and deep learning solutions. I specialize in computer vision tasks such as object detection, pose estimation, segmentation, and OCR, as well as generative AI including RAG, LLM agents, and GANs. I have built and deployed real-world applications using cutting-edge technologies such as YOLOv8, EasyOCR, MediaPipe, and StrongSORT, including license plate recognition systems, virtual mouse control, and PPE compliance for construction sites. With proficiency in designing and fine-tuning models using PyTorch, TensorFlow, and OpenCV, I focus strongly on performance and accuracy. I am experienced in developing generative AI applications with LangChain, LangGraph, and LlamaIndex, including PDF-based Q&A bots, smart assistants, and self-reviewing email writers. I am skilled with cloud deployment, Streamlit, Docker, and scalable data pipelines, and excel at collaborating in agile teams to continuously improve models through active learning, data annotation, and evaluation.

Available to hire

I am a motivated and results-driven AI Engineer with hands-on experience in developing, deploying, and optimizing end-to-end machine learning and deep learning solutions. I specialize in computer vision tasks such as object detection, pose estimation, segmentation, and OCR, as well as generative AI including RAG, LLM agents, and GANs. I have built and deployed real-world applications using cutting-edge technologies such as YOLOv8, EasyOCR, MediaPipe, and StrongSORT, including license plate recognition systems, virtual mouse control, and PPE compliance for construction sites.

With proficiency in designing and fine-tuning models using PyTorch, TensorFlow, and OpenCV, I focus strongly on performance and accuracy. I am experienced in developing generative AI applications with LangChain, LangGraph, and LlamaIndex, including PDF-based Q&A bots, smart assistants, and self-reviewing email writers. I am skilled with cloud deployment, Streamlit, Docker, and scalable data pipelines, and excel at collaborating in agile teams to continuously improve models through active learning, data annotation, and evaluation.

Skills

Experience Level

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Intermediate

Intermediate

Language

Arabic

Fluent

English

Advanced

Work Experience

Computer Vision Freelancer

September 1, 2024 - Present

Built an end-to-end image classification pipeline for academic PDFs by scraping data from Arxiv, converting PDF pages to images, and training a model to detect page type and orientation. Developed a real-time safety compliance system for construction sites using combined pose estimation and object detection (YOLOv8) to monitor PPE usage and worker count. The system was deployed via Streamlit dashboard and Docker for visualization and scalability. Implemented a crack segmentation and measurement system that translates pixel-level segmentation masks into real-world area metrics and exports results as CSV files with visual reports for inspection teams. Created a custom OCR pipeline for German-language invoices, extracting structured data using image preprocessing and text parsing techniques.

Generative AI Trainee at Digital Egypt Builders Initiative (DEBI) - Ministry of Communications and Information Technology, Egypt

September 1, 2024 - September 1, 2025

Gained advanced hands-on experience in computer vision, natural language processing, and generative AI through collaborative real-world projects. Developed NLP systems including sentiment analysis, named entity recognition, and text classification using Hugging Face Transformers. Applied prompt engineering techniques to optimize responses from large language models, including OpenAI APIs and custom vector-based retrieval. Co-developed a team-based Retrieval-Augmented Generation (RAG) system using LangChain and LLaMA to improve question-answering with external context. Built and trained advanced computer vision models such as Conditional GANs, Pix2Pix, and SRGAN for image generation and enhancement tasks.

Computer Vision Freelancer

September 1, 2024 - Present

Built an end-to-end image classification pipeline for academic PDFs by scraping data from Arxiv, converting PDF pages to images, and training a model to detect page type and orientation. Developed a real-time safety compliance system for construction sites combining pose estimation and object detection (YOLOv8) to monitor PPE usage and worker count. Deployed via Streamlit dashboard and Docker for easy visualization and scalability. Implemented a cracks segmentation and measurement system translating pixel-level segmentation masks into real-world area metrics (mm²) with CSV export and visual report generation for inspection teams. Created a custom OCR pipeline for German-language invoices extracting structured data through image preprocessing and text parsing techniques.

Generative AI Trainee at Digital Egypt Builders Initiative (DEBI) - Ministry of Communications and Information Technology

September 1, 2024 - September 1, 2025

Gained advanced hands-on experience in computer vision, natural language processing (NLP), and generative AI through collaborative real-world projects. Developed NLP systems including sentiment analysis, named entity recognition (NER), and text classification using Hugging Face Transformers. Applied prompt engineering techniques to optimize responses from large language models including OpenAI’s APIs and custom vector-based retrieval. Co-developed a team-based Retrieval-Augmented Generation (RAG) system using LangChain and LLaMA to improve question-answering with external context. Built and trained advanced computer vision models including Conditional GANs, Pix2Pix, and SRGAN for image generation and enhancement tasks. Followed agile methodologies using Git and GitHub for version control, code reviews, and collaborative development. Delivered technical presentations focusing on model performance, explainability, and deployment readiness.