AI / ML Engineer | LLMs · RAG · CV
I Build Intelligent Systems That Scale.
AI/ML Engineer with 2+ years of experience building end-to-end AI systems. Specialized in LLMs, Computer Vision, and MLOps. Graduated with A+ honors.
AI/ML Engineer with 2+ years of experience building end-to-end AI systems. Specialized in LLMs, Computer Vision, and MLOps. Graduated with A+ honors.
Deep dives into production-grade AI applications with video demonstrations.
Graduation Project (Grade: A+). End-to-end AI recruitment platform using semantic search and RAG to match candidates with job descriptions. Features a real-time AI interview coach.
Real-time fruit quality grading system. Multi-stage pipeline: detection (YOLOv8), classification (EfficientNet-B4), and size estimation — achieving sub-100ms inference.
Production-ready machine learning engine for financial risk assessment. Integrated with SHAP for explainability and Streamlit for real-time dashboarding.
Fully Private Document Intelligence Platform. AI-powered system combining hybrid search (semantic & BM25), Late Chunking, and intelligent routing for on-premise RAG via local LLMs (Ollama).
A collection of research and development projects across various AI sub-fields.
Predictive modeling, classification, and optimization projects.
View 8+ Projects →
Neural networks, CNNs, GANs, and transfer learning experiments.
View 15+ Projects →
LLM fine-tuning, image generation, and multimodal AI agents.
View 10+ Projects →
Text analysis, speech-to-text, and semantic understanding systems.
View 4+ Projects →Delivering high-impact AI and software engineering solutions tailored to business needs.
Develop intelligent systems that enhance your business using AI and machine learning techniques, including AI agents, automation, chatbots, image classification, and predictive models.
Integrate your applications with powerful backends using Django, FastAPI frameworks, and create robust RESTful APIs.
Build modern, responsive websites for your business using the latest technologies and frameworks with user-friendly interfaces.
Deploy and host your applications on cloud platforms like AWS, DigitalOcean, Heroku, or Vercel, ensuring high availability and scalability.
Get expert guidance on AI and web development projects, from initial planning to deployment, ensuring your solutions are efficient and effective.
A comprehensive toolkit for architecting and deploying production-grade AI systems.
My end-to-end approach to building and deploying robust AI systems.
Curating, cleaning, and augmenting datasets for high-quality training.
Selecting architectures (Transformers, CNNs) based on task requirements.
Experiment tracking with MLflow and multi-metric evaluation (mAP, F1).
Containerization with Docker and deployment via FastAPI & Cloud APIs.
I am an AI / Machine Learning Engineer dedicated to bridging the gap between theoretical research and production-grade applications.
With a solid academic foundation from EELU, graduating with A+ honors, my journey in AI has been driven by a passion for solving complex, real-world problems. I don't just build models; I architect end-to-end intelligent systems that are scalable, explainable, and high-performing.
My expertise lies at the intersection of Large Language Models (LLMs) and Computer Vision. I have a deep fascination with RAG (Retrieval-Augmented Generation) architectures, where I specialize in building systems that can "reason" over private data with high precision. In the realm of Computer Vision, I focus on real-time inference and multi-stage pipelines that combine detection (YOLOv8) with fine-grained classification (EfficientNet).
Beyond the algorithms, I am a firm believer in MLOps best practices. I ensure that every project I work on is containerized (Docker), versioned (MLflow), and ready for the cloud (AWS/GCP). My goal is to always deliver "Intelligence as a Service" that adds tangible value to businesses and users alike.
Graduated with A+ honors from EELU. Specialized in Advanced ML and Software Engineering.
Expertise across the entire lifecycle: Data Prep, Model Design, Training, and MLOps Deployment.
A journey of technical contribution, leadership, and community impact in the AI space.
Smart Village, Giza, Egypt
United States
Participated in a remote, self-paced educational AI internship focused on achieving General AI Fluency. This program emphasizes practical AI work with a collaborator mindset, focusing on prompt engineering, critical evaluation of AI outputs, and the responsible use of generative AI tools.
Key responsibilities and achievements include:
Contributed to organizing AI-focused technical events and workshops while collaborating on Machine Learning and Generative AI initiatives. Worked on fostering a community of AI enthusiasts and bridging the gap between academic theory and practical implementation.
A comprehensive collection of 40+ industry-recognized credentials in AI, ML, and Software Engineering.
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Everything you need to know about working together on your next AI project.
I specialize in Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), Computer Vision (YOLOv8, EfficientNet), and MLOps (Docker, MLflow, AWS). My focus is on building systems that are production-ready and scalable.
Absolutely. I provide end-to-end development, from architectural design and data engineering to model training and cloud deployment. I ensure your AI solution is not just a prototype but a robust application.
Project timelines vary based on complexity. Simple AI integrations typically take 1-2 weeks, while complex full-stack AI applications can take 4-8 weeks. I provide detailed timelines after understanding your specific requirements.
Yes. I offer monitoring, model retraining, and infrastructure management to ensure your AI systems stay accurate and efficient post-launch. AI models require continuous monitoring to handle data drift.
My solutions focus on scalability and production-readiness. I don't just build models; I build robust pipelines that integrate seamlessly with your existing infrastructure, focusing on low latency and cost optimization.
Let's discuss how I can add value to your AI engineering team.
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