Machine learning platform engineer in payments

Mollie; Amsterdam; On-site; EUR 70,000 - 110,000; Full time

Job summary

Mollie is seeking a Machine Learning Platform Engineer to join the Machine Learning Platform team within the Data Domain. You will collaborate with ML Platform Engineers, ML Scientists, and domain engineers to deliver scalable ML solutions across Mollie.

You\'ll deploy models to production on GCP, develop CI/CD pipelines, manage Kubernetes endpoints, and contribute to tooling such as LiteLLM and LibreChat while advancing MLOps, observability, and automated retraining.

Qualifications

• 1+ year of experience deploying and maintaining ML models in production.
• Hands-on Python experience with ML libraries and data tooling.
• Familiarity with GCP and containerization (Docker).
• Plus: Kubernetes and Terraform for IaC.

Responsibilities

• Collaborate with ML Platform Engineers, ML Scientists, and engineers to deliver scalable ML solutions.
• Deploy and operationalize ML models to production in partnership with ML Scientists.
• Enhance and maintain Mollie\'s cloud-based ML Platform on GCP, writing production-grade Python and Terraform daily.
• Build and maintain CI/CD pipelines for ML training and inference workflows.
• Deploy, manage, and scale model serving endpoints on Kubernetes for low-latency inference.
• Contribute to hosting and extending open-source AI tooling (e.g., LiteLLM, LibreChat).
• Champion MLOps practices, including model versioning, experiment tracking, and data validation.
• Ensure platform reliability with observability, monitoring, and alerting for infrastructure and models.
• Support and expand generative AI capabilities within Mollie.

Skills

MLOps concepts

CI/CD for ML

Python programming

Tools

scikit-learn

pandas

NumPy

XGBoost

LightGBM

MLflow

Docker

Job description

Описание:

We are looking for a Machine Learning Platform Engineer to join Mollie's Machine Learning Platform team, sitting within our broader Data Domain.

Задачи:

• 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.

Требования:

• 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)


• Strong context-switching ability with sharp attention to detail, adapting quickly to shifting priorities


• Experience building and maintaining CI/CD pipelines for ML workflows


• Будет плюсом: preferred familiarity in container orchestration tools such as Kubernetes and Kubeflow; Preferably familiarity with infrastructure-as-code (IaC) tools such as Terraform

Условия:

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. you'll be supported with the tools, trust and opportunities to grow your way.