Laurynas Stašys
Laurynas is a machine learning engineer who has been working in the field for the last 10 years focusing on different data problems in verticals of telecommunications, human resources, cybersecurity and devops. He has great passion in automating ML pipelines and is a strong believer in the value of data. Most recently, he has been working in CAST AI where he spent great deal of time of making Kubernetes automation more intelligent using various methods of machine learning.
Session
In today’s fast-paced machine learning environment, the ability to efficiently manage and reuse features across multiple models is crucial. This workshop explores how leveraging a feature store can streamline ML pipelines by ensuring consistency and accelerating deployment cycles.
Participants will gain hands-on experience with setting up, managing, and integrating feature stores into their existing workflows—transforming raw data into valuable, production-ready features.