Scaling up ML Models to Multiple Brands
At Ahold Delhaize, we have multiple brands in different countries and many of them want to have similar ML models running on their websites. We would like to show, how we create a system that allows us to deploy the same model for different brands, without reinventing the wheel.
The components we developed for reusability
- Configurable central python package for each model
- Cookiecutter template to create repositories with necessary components
- Reusable pipelines to deploy models
- Identical infrastructure& service user setups
Basak Eskili is a Machine Learning Engineer at Ahold Delhaize. She is working on creating new tools and infrastructure that enable data scientists to quickly operationalise algorithms. She is bridging the space between data scientists and platform engineers while improving the way of working in accordance with MLOps principles. In her previous role, she was responsible for bringing models to production. She focused on NLP projects and building data processing pipelines. Basak also implemented new solutions by using cloud services for existing applications and databases to improve time and efficiency.