Real-Time Feature Aggregation at Scale: iFood’s Path to Sub-Sec Latency - Feature Store Summit 2025

At iFood, real-time ML features are essential for delivering personalized and responsive user experiences across critical use cases such as fraud detection, recommendations, and promotions. In this talk, we’ll walk through how we built a low-latency feature platform that aggregates and serves features in under one second using Spark Structured Streaming and Redis. The platform enables real-time updates that power models reacting instantly to user behavior, supporting high-throughput, low-latency pipelines in a production environment. About the Speaker: Machine Learning Platform Lead at iFood, focused on building and scaling in-house ML solutions for real-time workloads.