Yuval Gorchover
I'm the AI/ML Engineering Team Lead at Voyantis, where I act as a translator between data science, backend engineering, and business goals. My day-to-day involves overseeing our AI agent initiatives and building the shared infrastructure that powers them. I'm a big believer in finding the simplest path to a solution that works. I recently led our shift to a SQL-based ML architecture, which cut costs by 80% and onboarded customers 10x faster. I share these lessons in Towards Data Science and practice yoga - because debugging pipelines and holding a pose both require patience and balance.
Session
Production ML failures often stem from one overlooked issue: features that work perfectly in development break during inference. Through hands-on demonstration, this session shows how to eliminate feature drift using Feast's Python-based open source architecture. Learn to build reliable feature pipelines that maintain consistency across training and serving environments, ensuring your models perform as expected when deployed at scale.