Katerina Zanos is a Principal Machine Learning Engineer at The Walt Disney Company, building AI driven systems that shape how people discover and experience media at scale. Previously, she was a Senior Machine Learning Engineer at Meta, where she helped develop recommender models for Facebook Home Feed and Reels, focusing on deep learning architectures (including two tower networks) and approaches that improve relevance while giving new content its moment.
Before Meta, Katerina spent over five years at The New York Times, leading work on personalisation, newsroom messaging and audience growth tooling across search and social.
Upcoming Talks
13 May 2026
How do you modernize a recommendation system while the product keeps shipping? In this talk, Katerina will share how the team at ESPN evolved the app's personalization stack from heuristics to an ML-first recommender system, where each stage delivered value on its own while building toward the next.
She'll show where AI tooling acted as a force multiplier, compressing iteration cycles across documentation, evaluation, and debugging, and helping them spot impact, so they could focus on the right levers.
You'll leave with key takeaways on incremental modernization and where AI can truly accelerate your team's velocity.