Loblaws is one of Canada’s largest grocery store chains, our team at Loblaw Digital runs several ML systems such as search, recommendations, inventory, and labor prediction on production. In this talk, Mefta shares their experience setting up their ML platform on GCP using Vertex AI and open-source tools. The goal of this platform is to help all the data science teams within their organization to take ML projects from EDA to production rapidly while ensuring end-to-end tracking of these ML pipelines. Mefta also talks about their overall platform architecture and how the MLOps tools fit into the end-to-end ML pipeline.
In this episode
Senior ML Engineer, Loblaw Digital
Mefta Sadat is a Senior ML Engineer at Loblaw Digital. He has been here for over three years building the Data Engineering and Machine Learning platform. He focuses on productionizing ML services, tools and data pipelines. Previously Mefta worked at a Toronto based Video Streaming Company and designed and built the recommendation system for the Zoneify App from scratch. He received his MSc in Computer Science from Ryerson University focusing on research to mitigate risk in Software Engineering using ML.
Demetrios is one of the main organizers of the MLOps community and currently resides in a small town outside Frankfurt, Germany. He is an avid traveller who taught English as a second language to see the world and learn about new cultures. Demetrios fell into the Machine Learning Operations world, and since, has interviewed the leading names around MLOps, Data Science, and ML. Since diving into the nitty-gritty of Machine Learning Operations he felt a strong calling to explore the ethical issues surrounding ML. When he is not conducting interviews you can find him making stone stacking with his daughter in the woods or playing the ukulele by the campfire.
Vishnu Rachakonda is the operations lead for the MLOps Community and co-hosts the MLOps Coffee Sessions podcast. He is a machine learning engineer at Tesseract Health, a 4Catalyzer company focused on retinal imaging. In this role, he builds machine learning models for clinical workflow augmentation and diagnostics in on-device and cloud use cases. Since studying bioengineering at Penn, Vishnu has been actively working in the fields of computational biomedicine and MLOps. In his spare time, Vishnu enjoys suspending all logic to watch Indian action movies, playing chess, and writing.