MLOps Journey at Wolt
Speaker

From Android developer to Data Scientist to Machine Learning Engineer, Stephen has a wealth of software engineering experience. He believes that machine learning has a lot to learn from software engineering best practices and spends his time making ML deployments simple for other engineers. Stephen is also a founding member and organizer of the MLOps.community Meetups in Berlin.
SUMMARY
Forecasting supply and demand, serving restaurant recommendations, and predicting delivery times. These are just a few examples of how Machine Learning is being applied at Wolt. Now with over 20 million users, scaling the ML infrastructure has been a significant challenge.
This talk highlights those challenges and how they were addressed by building an end-to-end MLOps platform on Kubernetes. You'll learn about the open-source frameworks that Wolt integrated, specifically Flyte, MLFlow, and Seldon Core.

