Summary
Raouf Keskes is an AI Research Engineer with eight years of experience building end-to-end ML pipelines and deploying research-grade models in production environments. Currently at InstaDeep, he bridges theory and practice—designing algorithms, implementing scalable training/inference workflows, and containerizing solutions for GPU clusters and SLURM-managed HPC. His background in XAI produced a novel method (CAMEL) addressing limitations of popular interpretability techniques, and at MAbSilico he shipped practical tools for antibody binding-site prediction and protein file manipulation. Comfortable translating complex research into readable code and clear explanations, he combines rigorous academic training from Sorbonne with hands-on experience across sequence/structure biology and computer vision. Notably, he iterates between deep dives into papers and coding experiments to stay at the cutting edge of fast-moving AI research.
8 years of coding experience
5 years of employment as a software developer
Bachelor's degree, Mathematics and Computer Science, (Distinction), Bachelor's degree, Mathematics and Computer Science, (Distinction) at Université des Sciences et de la Technologie 'Houari Boumediène'
Engineering Master's degree, Artificial Intelligence, 15/20 (High honours), Engineering Master's degree, Artificial Intelligence, 15/20 (High honours) at Sorbonne University
Bachelor's degree, Computer Science, 15/20 (High honours), Bachelor's degree, Computer Science, 15/20 (High honours) at Pierre and Marie Curie University
French, Arabic, English