Summary
Ghali Chraïbi is a Data Scientist based in Lausanne with 8 years of experience applying machine learning and data engineering to real-world problems across public health, content moderation, and AI safety. Trained at EPFL (MSc Data Science), he combines rigorous research—demonstrated by a high-impact internship exposing LLM safety vulnerabilities—with hands-on production work like improving object-detection and audio moderation pipelines in industry. He has delivered analytics and automation tools used by operational teams (e.g., Covid contact-tracing workflows) and built evaluation frameworks and taxonomy-driven methods to make model behavior more explainable and robust. Ghali excels at bridging academia and industry, acting as data liaison on large-scale educational studies and turning research insights into deployable systems. Notably, his work on prompt-alteration attacks increased bypass rates by 66%, highlighting a rare mix of adversarial thinking and pragmatic engineering. He is passionate about trustworthy ML and building measurable, production-ready solutions that surface meaningful insights.
8 years of coding experience
3 years of employment as a software developer
Matura certificate, Applied Mathematics, Matura certificate, Applied Mathematics at Gymnase de Chamblandes
Bachelor of Science - BS, Communication Systems, Bachelor of Science - BS, Communication Systems at Ecole polytechnique fédérale de Lausanne
Master of Science - MS, Data Science, 5.39/6, Master of Science - MS, Data Science, 5.39/6 at EPFL (École polytechnique fédérale de Lausanne)
French, English, German, Japanese, Arabic