Machine Learning Platform Engineer I

About the Position

Your Opportunity

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.

Responsibilities

As an ML Platform Engineer, you will:

• 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

Requirements

• 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 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

We Offer

At Mollie, growth is personal. We believe everyone should have the chance to develop their skills, explore new challenges, and shape their career on their own terms.

You'll get regular feedback and performance reviews to support your development, with fair and transparent salary reviews along the way. Many Mollies move into new roles or take on new projects to stretch themselves, and we actively hire from within to help you take the next step.

No matter if you're aiming for promotion, exploring a different career path, or building new skills, you'll be supported with the tools, trust, and opportunities to grow your way.

Unlock your full potential and join us to eliminate financial bureaucracy. If you're excited by the idea of building what's next, for yourself and for thousands of businesses across Europe, we'd love to hear from you.

Benefits

• 20 days working from abroad
• Enjoy the flexibility to work from abroad for 20 days a year (excl high risk countries)
• Wellbeing Budget
• Enjoy €60 per month net towards taking care of yourself
• Lifestyle and Health Support
• Reach out for coaching and support whenever you need it via OpenUp
• 26 holiday days
• Time to relax. Plus an extra 2 days off in between 27 and 31 December!
• Commute options
• Receive an NS Business Card and participate in our bike lease plan
• Birthday off
• It’s your special day! Why spend it at the office?
• WFH Equipment Budget
• One off budget of €400 for our new hires
• Hybrid working
• With WFH & Internet allowance at €60 a month
• Discounted Lunch
• Hot and cold meals plus snacks available each day for less than €4 and only pay when you use the service!
• Health Insurance
• Insure with ONVZ or receive €125 net towards your own insurance
• Annual Mollieverse event
• All Mollies get together, connect, and have fun

How we hire

Step 1

Apply

Our Talent Acquisition team and hiring manager will review your application, and respond within 2 weeks.

Step 2

Screening call

If you seem like a Mollie-in-the-making, we’ll invite you to a screening call so we can learn more about each other.

Step 3

Are you the one?

You'll have two or more interviews. And if it's a highly technical role, we'll also assess the specific skills you'll need.