MLOps Coffee Sessions #119 with Hien Luu, Sr. Engineering Manager of DoorDash, MLOps at DoorDash: 3 Principles for Building an ML Platform That Will Sustain Hypergrowth co-hosted by Skylar Payne.

// Abstract
Machine Learning plays a big part at DoorDash in terms of what they do on a daily basis. It powers many of their core infrastructures.  

When it comes to DoorDash's business, they have to be leveraging machine learning and it is such a huge piece of the business that it is critical.

// Bio
Hien Luu is an Engineering Manager at DoorDash, leading the Machine Learning platform team at DoorDash. He is particularly passionate about the intersection between Artificial Intelligence and Big Data. He is the author of the Beginning Apache Spark 3 book.  He has given presentations at various conferences like Data+AI Summit, MLOps World, Deep Learning Summit, and apply() conference.

// MLOps Jobs board  
https://mlops.pallet.xyz/jobs

MLOps Swag/Merch
https://mlops-community.myshopify.com/

// Related Links
engineering.linkedin.com/hadoop/user-engagement-powered-apache-pig-and-hadoop
* https://doordash.engineering/2020/07/20/enabling-efficient-machine-learning-model-serving/
* https://doordash.engineering/2020/11/19/building-a-gigascale-ml-feature-store-with-redis/
* https://doordash.engineering/2021/03/04/building-a-declarative-real-time-feature-engineering-framework/
* https://doordash.engineering/2021/05/20/monitor-machine-learning-model-drift/
* https://doordash.engineering/2021/01/26/computational-graph-machine-learning-ensemble-model-support/

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Connect with Demetrios on LinkedIn: https://www.linkedin.com/in/dpbrinkm/
Connect with Skylar on LinkedIn: https://www.linkedin.com/in/skylar-payne-766a1988/
Connect with Hien on LinkedIn: https://www.linkedin.com/in/hienluu/

Timestamps:
[00:00] Introduction of DoorDash team
[01:58] Overview of DoorDash
[03:32] DoorDash's platform
[13:23] Experimenting and testing new models
[15:15] Experience transferring
[17:16] Effective engagement with customers
[24:15] Team sizes
[25:37] Metrics
[33:25] App for users
[34:04] Using Databricks and Snowflake together
[37:49] Supporting power users
[40:17] Advice and experiences
[43:53] Wrap up