Machine learning platform engineer in payments

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

• 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.

• 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)
• 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

• 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.