Machine Learning Platform Engineer I

Mollie; Amsterdam; Hybrid; EUR 90,000 - 130,000; Full time

Benefits offered by this job

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

Job summary

Mollie is seeking a Machine Learning Platform Engineer to join the ML Platform team within the Data Domain. You will help scientists deploy ML solutions at scale across risk, payments, and other domains.

Based at Mollie’s Lisbon Hub with a distributed team across Amsterdam and Lisbon, you will write production-grade Python and Terraform, build CI/CD pipelines, and manage Kubernetes endpoints in a hybrid environment.

Qualifications

• 1+ year of deploying and maintaining ML models in production.
• Solid understanding of MLOps: experiment tracking, reproducibility, and monitoring.
• Strong Python programming with ML/data libraries.

Responsibilities

• Collaborate with ML Platform Engineers and domain teams to deliver scalable ML solutions.
• Deploy and operationalize ML models to production in partnership with scientists.
• Enhance and maintain our cloud-based ML Platform on GCP with Python and Terraform.
• Build and maintain CI/CD pipelines for ML workflows.
• Deploy, manage, and scale model serving endpoints on Kubernetes.
• Develop and host custom GenAI tooling and platforms for internal teams and customers.
• Champion MLOps best practices including versioning, tracking, data validation, and retraining.
• Ensure platform reliability with observability, monitoring, and alerting.

Skills

Python

Terraform

GCP

Kubernetes

Kubeflow

Docker

CI/CD

MLOps

MLflow

Observability

Tools

Kubeflow

Terraform

Docker

Job description

Mollie is looking for a Machine Learning Platform Engineer to join the Machine Learning Platform team within the broader Data Domain. The team empowers Machine Learning Scientists to develop and deploy custom ML solutions at scale across 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, it maintains and continuously enhances the platform to keep it reliable, scalable, and fit for production-grade workloads. The team also works closely with domain teams to bring custom ML models into products and develops custom GenAI tooling and platforms for both internal employees and customers.

This is a hands‑on role where you will spend most 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.

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.

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 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