The bumpy road of bringing a machine learning model from development to production  - Ryan Ginstrom
Channel: FOSSASIA
Date: 25/08/2023

We will report on our journey from developing and deploying a machine learning model in the search space for the biggest C2C e-commerce marketplace in Japan. This talk will focus on the MLOps side of this journey (with a separate one focusing on the machine learning part).

In particular, we will discuss the following topics:

Using ML in a “traditional” search infrastructure

Architecture overview
Data engineering
ETLs
Training pipelines
Serving in production
Strict latency requirements
Timeouts and failsafes
Caching
“Productionalization”
Logging
Monitoring
Metrics
A/B testing with ML
Moving from “homegrown” model server to Seldon for model serving

Our learnings and key takeaways

During all the steps, we have used open source tools for the development and deployment.

Ryan Ginstrom
Machine Learning Engineer, Mercari
I am a machine learning engineer with a software engineering background. I have been working at Mercari as a machine learning engineer for 1.5 years.

Teo Narboneta Zosa
ML Engineer, Mercari, Inc.
Teo is a machine learning engineer in the AI & Search division of Mercari, Japan’s largest C2C marketplace. He is currently working across various business-critical projects and helping establish foundational MLOps processes and best practices across the org.