Sara Robinson is a Developer Advocate for Google Cloud, focusing on machine learning. Her work sits at the boundary between engineering and education: she inspires developers and data scientists to integrate ML into their applications through hands-on demos, online content, and events, turning cloud ML tooling into something practitioners can actually build with.

Sara is a co-author of the O’Reilly book Machine Learning Design Patterns, alongside Valliappa Lakshmanan and Michael Munn. The book captures tried-and-proven solutions to recurring challenges in data preparation, model building, and MLOps, from rebalancing skewed datasets to workflow pipelines and feature stores. She has shared these patterns with audiences at conferences, including a talk at the DataTalks.Club conference in February 2021.

Before joining Google Cloud, Sara was a Developer Advocate on the Firebase team, where she focused on making mobile and web development tools easier to use. She holds a bachelor’s degree from Brandeis University. When she is not writing code, she can be found on a spin bike or eating frosting.