Carrie Grimes Bostock is a Google Fellow in Technical Infrastructure, responsible for bringing cutting edge AI from research to production for products, from frameworks and applied AI to serving optimization and infrastructure support. She works closely with Google Deep Mind teams and many of Google products to create the best end results for ML and AI.

Prior to her current role, Dr. Grimes Bostock spent many years leading a research and technical team in Search at Google trying to figure out what criteria make a search engine index "good," "fast," and "comprehensive" – and how to achieve those goals through better index selection, crawl scheduling, and ranking, After that, she worked in Technical Infrastructure at Google as the Area Technical lead for fleet performance, forecasting, deployment and compute optimization.

Carrie Grimes Bostock graduated from Harvard with an A.B. in Anthropology/Archaeology in 1998, and an interest in quantitative methods for dealing with disparate data. She graduated from Stanford in 2003 with a PhD in Statistics after working with David Donoho on Nonlinear Dimensionality Reduction problems, and has been at Google since mid-2003.