Tecton

Evolution and Unification of Pinterest ML Platform

apply(conf) - Apr '21 - 10 minutes

As Pinterest grew over time, machine learning use cases proliferated organically across multiple teams, leading to a proliferation of technical approaches with bespoke infrastructure. The ML Platform team has been driving Pinterest Engineering to a unified platform to tame the complexity of these diverse use cases. This talk will give a brief history of the evolution of Pinterest ML and our layer-by-layer approach to standardization, including a unified feature representation, shared feature store, and standardized inference services. Finally, we share lessons learned in aligning multiple engineering orgs on a shared ML vision in the face of typical resource constraints and competing priorities.
David Liu

Head of ML & Signal Platforms

Pinterest

David is an engineering manager for ML & Signal Platforms at Pinterest. His team provides unified infrastructure for 100+ ML engineers, used in applications spanning ads, recommendations, search, and trust/safety. These large-scale systems handle datasets of billions of events per day. Previously at Pinterest, David started the recommendations and visual search teams and built one of the first ML-based recommender systems in the product. He completed his bachelor's and master's degree in computer science at Stanford

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Unfortunately, Tecton does not currently support these clouds. We’ll make sure to let you know when this changes!

However, we are currently looking to interview members of the machine learning community to learn more about current trends.

If you’d like to participate, please book a 30-min slot with us here and we’ll send you a $50 amazon gift card in appreciation for your time after the interview.

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Interested in trying Tecton? Leave us your information below and we’ll be in touch.​

Unfortunately, Tecton does not currently support these clouds. We’ll make sure to let you know when this changes!

However, we are currently looking to interview members of the machine learning community to learn more about current trends.

If you’d like to participate, please book a 30-min slot with us here and we’ll send you a $50 amazon gift card in appreciation for your time after the interview.

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or

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