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Machine Learning Platform Engineer I

Portugal, Lisbon · Job Posted July 04, 2026
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Job Description

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.

Job Responsibility

  • 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
  • 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
  • Deploy, manage, and scale model serving endpoints on Kubernetes
  • Assist in extending, developing, and hosting custom and open-source AI tooling
  • Champion MLOps best practices
  • Ensure platform reliability by setting up observability, monitoring, and alerting
  • Maintain and enhance open-source AI tooling hosted at Mollie

Requirements

  • 1+ year of experience deploying and maintaining ML models in production
  • Good understanding of MLOps principles, including 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 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
  • Preferably familiarity with infrastructure-as-code (IaC) tools such as Terraform
  • Experience building and maintaining CI/CD pipelines for ML workflows

What we offer

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

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