Scaling the Machine Learning Platform at DoorDash
YOW! Data 2021
DoorDash’s mission is to grow and empower local economies. DoorDash’s business is a 3-sided marketplace composed of Dashers, consumers, and merchants.
As DoorDash's business grows, it is essential to establish a centralized ML platform to accelerate the ML development process and to power the numerous ML use cases. We are making good progress, but we are still in the early days of building out our ML platform.
This presentation will detail the DoorDash ML platform journey that includes the way we establish a close collaboration and relationship with the Data Science community, how we intentionally set the guardrails in the early days to enable us to make progress, the principled approach of building out the ML platform while meeting the needs of the Data Science community, and finally the technology stack and architecture that powers billions of predictions per day and supports a diverse set of ML use cases. They include search ranking, recommendation, fraud detection, food delivery assignment, food delivery arrival time prediction, and more.
Head of Machine Learning Infrastructure
Hien Luu is a Sr. Engineering Manager at DoorDash, leading the Machine Learning Platform team. He is particularly passionate about the intersection between Big Data and Artificial Intelligence. He is the author of the Beginning Apache Spark 2 book. Teaching is one his passions and he is currently teaching Apache Spark course at UCSC Silicon Valley Extension school. He has given presentations at various conferences like QCon SF, QCon London, Hadoop Summit, JavaOne, ArchSummit and Lucene/Solr Revolution.