Summary
Ian Benlolo is a Machine Learning Specialist at Updata with eight years of experience bridging research and production in computer vision and materials-focused ML. He holds a Master's in Condensed Matter and Materials Physics from the University of Ottawa and translated that domain expertise into practical ML workflows while a Visiting Scholar at the National Research Council and CLEAN lab, accelerating materials design with GNNs and generative approaches. Ian has built large-scale fraud detection pipelines during an ML engineering internship at Cash App, applying self-supervised embeddings and production-ready model tooling to process millions of records. Based in Montreal, he combines a physics-first mindset from McGill with hands-on experience deploying end-to-end ML systems, making him adept at turning complex scientific problems into scalable, real-world solutions. An understated strength is his ability to move seamlessly between experimental research and robust engineering, often surfacing novel ML methods for domain-specific challenges.
7 years of coding experience
1 year of employment as a software developer
Bachelor of Applied Science (B.A.Sc.), Bachelor of Applied Science (B.A.Sc.) at Vanier College
Master's degree, Condensed Matter and Materials Physics, Master's degree, Condensed Matter and Materials Physics at University of Ottawa
Bachelor of Applied Science (B.A.Sc.), Physics and Computer Science, Bachelor of Applied Science (B.A.Sc.), Physics and Computer Science at McGill University
French, English