Summary
Hussein Hassan is a software engineer with 9 years of experience who blends a dual academic foundation in Computer Science and Applied Mathematics with hands-on AI and full-stack engineering. He has built production-ready ML and retrieval systems—from CNN-based real-time video analytics to RAG pipelines using Pinecone and OpenAI—demonstrating strength across model development, data engineering, and cloud-native deployments. A graduate of rigorous programs in Madrid and Zürich, he pairs quantitative rigor with practical product delivery, recently contributing to prototypes that improve semantic search and factual accuracy. Comfortable across Python, TensorFlow/PyTorch, React, Node.js, Docker, AWS and GCP, he moves solutions from research to scalable services. Based in Los Angeles, Hussein thrives in collaborative teams and continuously explores orchestration and LLM tooling like LangChain and LlamaIndex to push applied-AI boundaries. Notably, his background in economics and applied statistics informs predictive modeling work in finance and regulation-focused search systems.
9 years of coding experience
1 year of employment as a software developer
International Baccalaureate, International Baccalaureate at The British International School, Cairo
Bachelor of Applied Science - BASc, Computer Science & Applied Mathematics, Bachelor of Applied Science - BASc, Computer Science & Applied Mathematics at University of California, Los Angeles
English, Arabic, Spanish