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Improving Support for Deep Learning in Etsy’s ML Platform

Posted Mar 30, 2023 | Views 157
# Deep Learning
# Etsy
# ML Platform
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SPEAKER
Kyle Gallatin
Kyle Gallatin
Kyle Gallatin
Software Engineer for Machine Learning Infrastructure @ Etsy

Kyle Gallatin is currently a Software Engineer for Machine Learning Infrastructure at Etsy. He primarily focuses on operationalizing the training, deployment and management of machine learning models at scale. Prior to Etsy, delivered ML microservices and lead the development of MLOps workflows at the pharmaceutical company Pfizer. In his spare time, Kyle mentors data scientists and writes ML blog posts for Towards Data Science.

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Kyle Gallatin is currently a Software Engineer for Machine Learning Infrastructure at Etsy. He primarily focuses on operationalizing the training, deployment and management of machine learning models at scale. Prior to Etsy, delivered ML microservices and lead the development of MLOps workflows at the pharmaceutical company Pfizer. In his spare time, Kyle mentors data scientists and writes ML blog posts for Towards Data Science.

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SUMMARY

With the increasing number of deep learning models in production, Etsy faces new challenges in terms of scaling and managing the models. The talk highlights the custom feature transformations, ideal infrastructure settings, and early feedback loop on the latency of models as some of the challenges faced. Etsy has developed new processes and tooling to address these challenges and improve the performance of the platform.

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