Calvin Janitra Halim
Calvin is an ML engineer currently working at Mercari, where he focuses on creating and improving ML models and MLOps infrastructure to ensure the safety of Mercari users. Previously, he worked as an ML engineer at Rakuten, developing various projects such as inappropriate review detection and business impact analysis, along with the MLOps and DevOps infrastructure supporting these initiatives. He is passionate about AI, ML, MLOps, and web development. In his free time, he produces electronic music and plays jazz fusion sporadically with his bandmates.
Session
In the Mercari Group’s Trust and Safety ML Team, we provide solutions to ensure the safety of the users. Examples of the solutions we provide include anti-money laundering countermeasures, credit card fraud detection, and many others. Some of these solutions are powered by machine learning models. In order to be as reactive as possible to emerging frauds, it is important to streamline the model improvement and deployment processes. In this talk, we will explain our platform and automation, and how each element helps us rapidly deploy new countermeasures. We will cover all MLOps steps: experimentation, training/deployment, evaluation, and metric monitoring. We hope our talk benefits those integrating DevOps into their ML solutions or building ML platforms, especially with GCP’s Vertex AI.