Chime is a financial technology company founded on the premise that basic banking services should be helpful, easy, and free. Behind that simple promise is a sophisticated ML team that regularly deploys sophisticated models in production, including some that recently made the transition from batch to real-time data. In this session, Peeyush Agarwal and Akshay Jain – Chime’s ML Platform Team leads – will walk through a real-world example, showcasing what it took from a technical perspective to go real-time across the entire ML lifecycle. See how Chime successfully sped up model development and launch, all while ensuring robust ML monitoring and observability – and lessons learned along the way.
Speakers
Akshay Jain
Lead Software Engineer, ML Platform, Chime
Peeyush Agarwal
Lead Software Engineer, ML Platform, Chime
Peeyush Agarwal is Lead Software Engineer, ML Platform at Chime. He leads the team which enables Data Science all the way from exploration, model development & training to orchestrating batch & realtime 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 & recommendations. At Google, he also worked on ML powered Adaptive Brightness and Adaptive Battery which were launched in Android P. 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.
