MLOps at DoorDash
MLOps is one of the hottest topics being discussed in the ML practitioner community. Streamlining the ML development and productionalizing ML are important ingredients to realize the power of ML, however it requires a vast and complex infrastructure. The ROI of ML projects will start only when they are in production. The journey to implementing MLOps will be unique to each company. At DoorDash, we’ve been applying MLOps for a couple of years to support a diverse set of ML use cases and to perform large scale predictions at low latency. This session will share our approach to MLOps, as well as some of the learnings and challenges.
Hien Luu is a Sr. Engineering Manager at DoorDash, leading the Machine Learning Platform team. Hien is particularly passionate about the intersection between Big Data and Machine Learning infrastructure. Hien has given presentations at various conferences like Data + AI Summit, XAI Summit, MLOpsWorld, MLOps Salon, Apply(), YOW!, and QCon,