MLOps Salon: Applying MLOps at Scale - Scaling ML Platform Responsibly at DoorDash

Presented by: Hien Luu - Sr. Engineering Manager at DoorDash and Kornel Csernai - Software Engineer, Machine Learning Platform at DoorDash
DoorDash is a three-sided marketplace that consists of Merchants, Consumers, and Dashers. As DoorDash’s business grows, the ML Platform also needs to grow in a responsible way to meet the needs of the growing Data Science community. The ML Platform has grown and evolved tremendously over the last year. We've learned to collaborate closely with the DS community, worked through the scaling challenges, and steadily and incrementally evolved the platform. As the platform onboarded additional mission-critical use cases, we needed to ensure the integrity of those by applying ML observability best practices, such as feature and model monitoring, and continuous model training. In this session, we will share our ML platform journey and story, as well as technical details about how we worked through the scaling challenges and our approach to ML Observability.