Amsterdam, North Holland, Netherlands
AI engineer focused on what happens between "we have a model" and "it works in production." I've been putting ML systems into the real world for 7+ years; from classical ML through NLP, computer vision, and now agentic AI - long before MLOps had its own conference circuit. It's what I do at ML6, what I teach at ULiège (where I built an open-source MLOps course from scratch), and honestly what I do on weekends too - coding side projects, preparing lectures, or giving talks at conferences and meetups. The line between work and hobby blurred a while ago and I've stopped trying to fix it. Cloud-agnostic (GCP, AWS, Azure). I find the engineering around the model more interesting than the model itself.
Leading the design and delivery of advanced AI solutions including customer support chatbot, market modelling and customer profiling systems, agentic RAG architectures, and scaling AI products from MVP to production, while driving key pre-sales tracks and shaping our Agentic AI offering. Delivered these projects for customers such as Randstad, Nestlé, Mediahuis, Thyssenkrup, Scout24 and more.
As squad lead, I got the opportunity to guide and coach a pretty awesome team of ML and data experts. That means: - Being responsible for everybody's planning - Empower squad members, help them with personal growth - Support client projects within the squad
We accelerate intelligence, technology, customer value and people by using big data and cloud technologies to bring real world impact with Machine Learning. For me, this means: - As ML Engineer & tech lead: Help implement a variety of client projects. These include text classification, demand forecasting, root cause analysis with XAI, product recognition with Computer Vision and more. For clients such as Otary, TVH or Randstad. - As NLP and Structured Data expert chapter member: Track, experiment and share knowledge on the latest technology of these fields. - As Squad Lead: Manage team member's projects, planning and personal growth.
I'm in charge of the Machine Learning Systems Design (MLOps) course. I give it as an elective course, which represents 5 ECTS to M.Sc. students in Data Science and Computer Science.
Metyis (previously YGroup) is an ambitious consulting firm specializing in strategy and data science. I worked as a data scientist on solutions such as churn prediction and demand forecasting for Heineken, PVH, and Carlsberg.
Working on Philip's Lifeline Personal Emergency Repose System (PERS). My task consisted on improving the CareSage predictive analysis engine with text classification.