Motional's Blueprint for High-Performance ML Systems in Autonomous Driving

Learn how to transform ML development lifecycles for autonomous vehicle data processing through this 30-minute conference talk from Ray Summit 2025. Discover Motional's journey from legacy pipelines with manual processes and rigid architectures to a unified, horizontally scalable ML system built on Ray that processes terabytes of data in hours instead of weeks. Explore the challenges of static data replication, expensive distributed frameworks, and operational friction that previously slowed feature engineering and model iteration. Understand the blueprint for designing reliable, high-performance data processing pipelines for large-scale feature generation across Perception, Prediction, and Planning systems. Examine the migration from brittle staging-based implementations to fully autoscaled Ray architecture that reduces costs while empowering ML engineers with end-to-end workflow ownership. Master Motional's innovative "1-actor-per-node" Ray Actor pattern that brings compute to data and eliminates costly network communication, boosting performance while serving as a potential addition to official Ray Patterns documentation. Gain practical, proven strategies for building scalable, performant, and resilient ML systems capable of handling massive data challenges across various industries beyond autonomous driving.