Machine Learning Platform Engineer I

Posted 4 Hours Ago
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Amsterdam, NLD
Hybrid
Junior
Fintech • Payments • Software • Financial Services
The Role
Deploy and operationalize machine learning models, maintain Mollie’s GCP-based ML platform, and build production-grade Python and Terraform solutions. Responsibilities include CI/CD pipelines, Kubernetes model serving, MLOps standards, observability, monitoring, automated retraining, and hosting AI and generative AI tooling. The role collaborates with machine learning scientists and engineering teams to deliver scalable, reliable ML solutions.
Summary Generated by Built In

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.

Skills Required

  • At least 1 year of experience deploying and maintaining machine learning models in production
  • Understanding of MLOps principles, including experiment tracking, reproducibility, pipeline automation, model versioning, and production monitoring
  • Strong hands-on Python programming skills
  • Proficiency with scikit-learn, pandas, NumPy, XGBoost, LightGBM, and MLflow
  • Familiarity with a major cloud platform
  • Experience with Docker containerization
  • Experience building and maintaining CI/CD pipelines for ML workflows
  • Familiarity with GCP
  • Familiarity with Kubernetes and Kubeflow
  • Familiarity with Terraform or other infrastructure-as-code tools
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The Company
HQ: Amsterdam
904 Employees
Year Founded: 2004

What We Do

Mollie offers a single platform for businesses to get paid and manage their money. One that makes payments, reconciliation, reporting, fraud prevention, and financing simple for all – from startups to enterprises. Founded in 2004, Mollie’s mission is to make payments and money management effortless for every business in Europe. Our 750-strong team works from offices across the continent, including Amsterdam, Ghent, Lisbon, London, Maastricht, Milan, Munich, and Paris. Today, more than 250,000 businesses use Mollie to drive revenue, reduce costs, and manage funds.

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