Summary
Austin Tripp is a Senior Machine Learning Research Scientist with nine years of experience applying ML to chemistry, nanomaterials, and recommender systems, currently at Valence Labs in the UK. His work bridges academic rigor—PhD-level engineering research at Cambridge and hands-on experimental roles—with industry impact from internships and roles at Microsoft, NVIDIA, Wish, and CSIRO Data61. He has deep practical experience building ML-driven embeddings, retrosynthesis methods, and neural animation models, and has coordinated multidisciplinary teams to deliver demos and production research. Notably, his background spans wet-lab nanotech projects and large-scale ML experiments, giving him a rare fluency across physical sciences and applied machine learning. He maintains a public-facing portfolio at austintripp.ca that highlights research artifacts and reproducible code tying his chemistry-first ML work to real-world applications.
9 years of coding experience
3 years of employment as a software developer
Bachelor of Applied Science (BASc), Nanotechnology Engineering, Option in Mathematics, Bachelor of Applied Science (BASc), Nanotechnology Engineering, Option in Mathematics at University of Waterloo
Doctor of Philosophy - PhD, ENGINEERING, Doctor of Philosophy - PhD, ENGINEERING at University of Cambridge
Master of Divinity - MDiv, Underwater Basket Weaving, Marginal Pass, Master of Divinity - MDiv, Underwater Basket Weaving, Marginal Pass at Girton College
English, French, Esperanto, Chinese