These are the confirmed sessions for Airflow Summit 2026.

Title

Orchestrating 100 ML Models using Airflow

by Ryan Stevens

Productionizing ML workflows is complicated; scaling them is harder. At Ramp, we grew from zero to nearly 100 production ML models powering systems like credit risk assessment and sales lead valuation.

This talk covers how Airflow became the backbone of our ML platform, orchestrating ETL jobs, data quality checks, and model runs. We’ll discuss how we evolved it to meet the increasing complexity of our ML systems.

Every ML system consists of feature creation and large-batch inference. We started with a few DBT models and one cloud-hosted notebook, which evolved into thousands of upstream tables and hundreds of AWS batch inference jobs.