Ibotta has a wide variety of machine learning (ML) problems including recommendation engines, search relevancy, and pricing optimization. However the most important ability for Ibotta’s ML team is to minimize the time from ideation to production. Come learn how Ibotta’s ML team has invested in force multipliers to seamlessly traverse the end to end machine learning lifecycle to improve the app experience for a growing user base of over 25M. This talk will cover feature engineering, ML as software engineering, ML architecture, and the future vision for ML at Ibotta.

Additionally, you will hear from various Ibotta ML engineers on their experiences deploying ML models into high traffic production applications!

Speaker: Charley Frazier, Ibotta
https://www.linkedin.com/in/charley-frazier/