Machine Learning Platform Engineer

Who you are

• 1+ year of experience deploying and maintaining ML models in production
• Good understanding of MLOps principles, including matters such as experiment tracking, reproducibility, pipeline automation, model versioning, and monitoring in production
• Strong hands-on Python programming skills, with proficiency across common ML and data libraries such as scikit-learn, pandas, NumPy, XGBoost, LightGBM, and MLflow
• Familiarity with at a major cloud platform, preferably GCP
• Experience with containerization (Docker), with preferred familiarity in container orchestration tools such as Kubernetes and Kubeflow
• Strong context-switching ability with sharp attention to detail, adapting quickly to shifting priorities
• Preferably familiarity with infrastructure-as-code (IaC) tools such as Terraform
• Experience building and maintaining CI/CD pipelines for ML workflows

What the job involves

• We are looking for a Machine Learning Platform Engineer to join Mollie's Machine Learning Platform team, sitting within our broader Data Domain
• Our ML Platform empowers Machine Learning Scientists to develop and deploy custom ML solutions at scale across Mollie, serving domains including Risk & Fraud, Payments, Merchant Experience, Financial Services, Go-to-Market, and more
• As the central team responsible for Mollie's Machine Learning Platform, we own the maintenance and continuous enhancement of the platform, ensuring it remains reliable, scalable, and fit for production-grade workloads
• We work closely with domain teams to bring custom ML models into products, bridging the gap between research and real-world impact, while also designing and developing custom GenAI tooling and platforms for both internal employees and Mollie's customers
• This is a hands-on role where you will spend the majority of your time writing Python and Terraform alongside a team of skilled ML Platform Engineers
• Based at Mollie's Lisbon Hub, you will be part of a geographically distributed team spanning Amsterdam and Lisbon, working in a collaborative environment that embraces both remote and hybrid ways of working
• Collaborate closely with ML Platform Engineers, Machine Learning Scientists, and engineers across Mollie's domain teams to deliver scalable Machine Learning solutions
• Deploy and operationalize ML models to production in partnership with Machine Learning Scientists, bridging the gap between experimentation and real-world impact
• Enhance and maintain our cloud-based ML Platform on GCP, writing production-grade Python and Terraform daily
• Build and maintain CI/CD pipelines for ML model training and inference, ensuring reliable and automated workflows across environments
• Deploy, manage, and scale model serving endpoints on Kubernetes, ensuring low-latency, high-availability inference for production workloads
• Assist in extending, developing, and hosting custom and open-source AI tooling ; enabling teams to rapidly build and deploy AI-powered solutions
• Champion MLOps best practices, implementing standards around model versioning, experiment tracking, data validation, and automated retraining
• Ensure platform reliability by setting up observability, monitoring, and alerting for both infrastructure and deployed models
• Maintain and enhance open-source AI tooling hosted at Mollie (such as LiteLLM and LibreChat), and further support and expand our generative AI capabilities

Benefits

• Noise cancelling headphones
• MacBook
• Birthday off
• Complimentary baby days
• 20 days working from abroad
• 25 holiday days
• Commute reimbursement
• Work from home budget
• Bike lease plan
• Internet allowance
• In-office lunch
• Wellbeing program
• Pension contribution
• Health insurance
• Bonus scheme
• Equity plans
• Referral bonus
• Learning platform
• Mentor program