Eindhoven Data Community Meetup 17 - Picnic

We are very happy to announce that we are organising the 17th edition of the Eindhoven Data Community meetup together with our friends from Picnic! This time we will be back August 29th, at one of our favourite locations, the Skybar in Microlab!

Starting in one Dutch town in 2015, Picnic now serves over 60 cities in both the Netherlands and Germany. The secret to their success? An end-to-end business and a just-in-time supply chain. From the app-only store, forecasting of orders, warehouse fulfilment, to the evolving distribution strategy of their fleet of electric vehicles, they have build everything in-house on their own developed software. During the meetup, Sven and Job, both Machine Learning engineers at PicNic, will talk about their cloud agnostic, internal ML platform running on Kubernetes.

Talk 1: Optimizing Picnic's last mile delivery using our ML Platform
As an online supermarket and tech company, Picnic has more than 20 ML models in production. These models play a critical role in optimizing our supply chain and last-mile delivery logistics. In this talk, we will dive deeper into the stop-time model, which predicts our customer delivery times. Having an accurate forecast for our customer delivery times enables us to plan efficiently while still providing a pleasant customer experience. Furthermore, we will show how our internal ML platform enables us to run these models effortlessly and discuss our latest addition to the platform: the Feast feature store.

Talk 2: Are you ready for MLOps? 🫵
MLOps has survived the hype cycle and is gaining in maturity. But are we looking at MLOps for answers for the right things?
No matter how valuable MLOps can be for you, without proper building blocks in place MLOps cannot live up to its full potential. What are the prerequisites for MLOps? What parts of MLOps should you focus on? When should you even start thinking about MLOps, or when is ‘plain’ DevOps wiser to focus on first? Join us in this session to learn more!

Let's learn more about MLOps together! In this talk, we will share with you our take on when and why MLOps is relevant for you. So, you learn when and how to apply MLOps the right way to get most value out of it. Our collective experience entails multiple years of consulting companies on the topic, as well as teach trainings on MLOps. Having applied MLOps in many contexts and situations allowed us to see commonalities between them — and those we would like to share with you! Why? Because we love sharing knowledge!

Program

• 17:00 – 18:00: 🍕Pizza
• 18:00 – 18:10: 🎤 Welcome
• 18:10 – 19:00: 🎤 Sven Arends & Job Almekinders: Optimizing Picnic's last mile delivery using our ML Platform
• 19:00 – 19:15: ⏸️ Break
• 19:15 – 20:00: 🎤 Jeroen Overschie & Jetze Schuurmans - Are you ready for MLOps?
• 20:00-21:00: 🥤Drinks

Speaker 1: Sven Arends
Sven Arends is a ML Engineer at Picnic. Sven is currently responsible for Picnic’s ML models for the Distribution domain. These models forecast e.g. the amount of time needed to deliver our groceries at customers. Previously Sven worked as platform engineer leading the Kubernetes Accelerated Compute initative in Picnic and worked as a Data Scientist for a Finnish startup. Sven has holds a Computer Science MSc degree from the TU/e.

Speaker 2: Job Almekinders
Job Almekinders is a MLOps Engineer at Picnic, where he focuses on scaling and standardizing machine learning usage by building an internal ML platform. He has prior working experience as a Data Platform Engineer at HelloFresh and Data Engineering Consultant. Job holds a MSc degree in Data Science & Entrepreneurship from the Jheronimus Academy of Data Science (TU/e & TiU).

Speaker 3: Jeroen Overschie
Jeroen is a Machine Learning Engineer at Xebia Data (formerly GoDataDriven), in The Netherlands. Jeroen has a background in Software Engineering and Data Science and helps companies take their Machine Learning solutions into production.

Besides his usual work, Jeroen has been active in the Open Source community. Jeroen published several PyPi modules, npm modules, and has contributed to several large open source projects (Hydra from Facebook and Emberfire from Google). Jeroen also authored two chrome extensions, which are published on the web store.

Speaker 4: Jetze Schuurmans
Jetze is a well-rounded Machine Learning Engineer who is as comfortable solving Data Science use cases as he is productionizing them in the cloud. His interests include MLOps, GenAI and Cloud Engineering. As a researcher, he has published papers in Computer Vision, Natural Language Processing and Machine Learning in general. Jetze loves sharing knowledge during community events and by giving trainings.