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Islam Ouda

@islamouda

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I build end-to-end RAG applications with evaluation, monitoring, orchestration, and containerized deployment.

Palestine, State of

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What I'm looking for

I'm looking to contribute to AI/ML products where I can build reliable RAG and MLOps systems, strengthen my deployment and evaluation skills, and collaborate with teams that value Agile delivery, open source, and practical user impact.

I designed and shipped AI Cat Vet, an end-to-end Retrieval-Augmented Generation application that grounds LLM responses in veterinary case data. I built its retrieval, generation, automated evaluation, monitoring, and Docker-based deployment as a solo LLM Zoomcamp capstone project.

I improved held-out retrieval MRR from 0.80 to 0.856 through boosted field-weight search tuning, built LLM-as-a-judge model evaluation, and created a Grafana dashboard for cost, latency, relevance, and user feedback backed by PostgreSQL logging. I also designed a Kestra workflow and containerized the app, PostgreSQL, Grafana, and Kestra services for one-command deployment.

Beyond AI engineering, I served as Product Owner for MovePal, coordinating a six-person Agile team on a computer-vision rehabilitation application. I contribute to AutoEmulate, teach Java and OOP to peers, and create technical presentations focused on clear information architecture and data visualization.

Experience

Work history, roles, and key accomplishments

AI / ML Engineer

Self Employed

AI/ML engineer with hands-on experience building and shipping a complete Retrieval-Augmented Generation (RAG) application end to end, including retrieval, generation, automated evaluation, monitoring, and containerized deployment. Proficient in LLM APIs, vector/text search, MLOps tooling, and Docker-based deployment.