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Engineering Systems for Real-Time Predictions @DoorDash
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| by Raghav Ramesh Follow 0 Followers on Aug 22, 2018 | NOTICE: The next QCon is in London, Mar 4 - 6, 2019. Join us!

Raghav Ramesh presents DoorDash’s thoughts on how to structure machine learning systems in production to enable robust and wide-scale deployment of machine learning, and shares best practices in designing engineering tooling around machine learning.


Raghav Ramesh is a machine learning engineer at DoorDash working on its core logistics engine, where he focuses on AI problems: vehicle routing, Dasher assignments, delivery time predictions, demand forecasting, and pricing. Previously, he worked on various data products at Twitter, including recommendation systems, trends ranking, and growth analytics.

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