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Scaling Real-time Machine Learning at Chime

Posted Nov 22, 2022 | Views 570
# Lighting Talk
# ML Infrastructure
# Chime
# Arize.com
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Peeyush Agarwal
Lead Software Engineer, ML Platform @ Chime

Peeyush Agarwal is the Lead Software Engineer, ML Platform at Chime. He leads the team which enables data science all the way from exploration, model development, and training to orchestrating batch and real-time models in shadow and production. Earlier, Peeyush was a founding engineer in Chime's DSML team and worked on both building models and getting them into production.

Before Chime, Peeyush was a software engineer at Google where he developed unsupervised ML models that run on Google's data across search, Chrome, YouTube, and other properties to identify intent and use it for personalized ads and recommendations. At Google, he also worked on ML-powered Adaptive Brightness and Adaptive Battery which were launched into Android. Prior to joining Google, Peeyush was an entrepreneur who founded a customer engagement platform that counted Aurelia, Reebok, W, and Red Chief among its clients.

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Demetrios Brinkmann
Chief Happiness Engineer @ MLOps Community

At the moment Demetrios is immersing himself in Machine Learning by interviewing experts from around the world in the weekly MLOps.community meetups. Demetrios is constantly learning and engaging in new activities to get uncomfortable and learn from his mistakes. He tries to bring creativity into every aspect of his life, whether that be analyzing the best paths forward, overcoming obstacles, or building lego houses with his daughter.

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SUMMARY

In this Lighting Talk, Peeyush Agarwal explains 2 key pieces of the ML infrastructure at Chime. Peeyush goes into detail about the current feature store design and feature monitoring process along with the ML monitoring setup.

This Lighting Talk is brought to you by arize.com reach out to them for all of your ML monitoring needs.

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