Salim Virji and Carlos Villavieja, Google
Have you thought that your model trained on a Monday might not work on Saturday? Or that the model that you trained on users in Florida might not work for all Spanish-speaking users? In this talk, we present lessons learned from deploying and productionizing ML systems across various products at Google.
Salim Virji, Google
Salim Virji is a Site Reliability Engineer at Google, where he has built distributed compute, consensus, and storage systems.
Carlos Villavieja, Google
Carlos Villavieja is a Computer Architect/Researcher working as a Software/Site Reliability Engineer at Google. He works on Storage optimizations and his interests vary from micro-architecture to machine learning.
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author = {Salim Virji and Carlos Villavieja},
title = {Productionizing {Machine-Learning} Services: Lessons from Google {SRE}},
year = {2018},
publisher = {USENIX Association},
month = jun
}