Santiago Valdarrama is a computer scientist who has spent more than two decades building software, the last stretch of it focused on applied machine learning. He leads computer vision solutions at Levatas, where he manages a team of software engineers and machine learning engineers building real-world ML systems. He cares deeply about unlocking the power of technology for individuals and businesses, so they can use computers in ways that previously seemed unrealistic, and he is at his best in ambiguous problems that cannot be solved by a quick web search.

Santiago is also a builder of learning resources for the ML community. He co-founded Bnomial and co-authored Everyday ML Questions with Vladimir Haltakov, a project built around the idea of a small daily practice: one question at a time to help people build a durable machine learning habit. He has shared his roadmap for moving from software engineering into machine learning, including his seven practical lessons, at the DataTalks.Club conference and on the DataTalks.Club podcast.

Born in Cuba, where he earned his computer science degree, Santiago moved to the United States in 2009 and completed his master’s degree through Georgia Tech’s online computer science program. He shares practical machine learning content every day with a large audience on Twitter, and writes at his Underfitted newsletter.