Summary
Uong Lam is a machine learning engineer with 10 years of experience applying deep learning and NLP to products across industry and research, currently building his own project out of Vancouver. He has strong privacy-preserving ML and production experience from Google—working on differential privacy for YouTube Ads and demographic inference—and a track record of shipping search and recommendation models at Ericsson that improved engineer productivity. His background spans computational chemistry and molecular property prediction (state-of-the-art hydration free energy results) to nonprofit-focused ML at Keela and ML research at McGill, reflecting a rare blend of domain breadth. Comfortable across research and product delivery, he combines probabilistic methods (Gaussian processes) with scalable engineering of models and front-end integrations. Reachable at lam.uong2@mail.mcgill.ca, he often bridges applied ML problems that cross privacy, scientific modeling, and large-scale retrieval.
10 years of coding experience
7 years of employment as a software developer
Bachelor's Degree Joint Major in Computer Science and Biology, Bachelor's Degree Joint Major in Computer Science and Biology at McGill University