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MOMollie logo

Mollie

Location not stated

Machine Learning Platform Engineer I.

JUNIOR LEVELDATA & ML

Machine Learning Platform Engineer I

Machine Learning Platform Engineer I

Lisbon

Engineering

Machine Learning

FullTime

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.

What you’ll be doing

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.

What you'll bring

  • 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

Grow your way

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.

AI at Mollie

We believe in Always Be Shipping, and AI brings that philosophy to life across every team, every role, every day.

AI is core to how we build. It helps us move faster, simplify work and make smarter decisions, creating real impact for the businesses we serve. We're looking for people who are excited to use AI to shape the future of finance with us.

Benefits

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

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

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.

Pay
Not stated
Where
Not stated
Work
Not stated
Type
Not stated
Posted
15 Oct, 2026
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