Machine Learning Platform Engineer I

Stack

Responsibilities

• ▹collaborate with ML Platform Engineers, ML Scientists and domain engineers to deliver scalable ML solutions
• ▹deploy and operationalize ML models to production
• ▹enhance and maintain the cloud-based ML Platform on GCP, writing Python and Terraform daily
• ▹build and maintain CI/CD pipelines for ML training and inference
• ▹deploy, manage and scale model serving endpoints on Kubernetes
• ▹help develop and host custom and open-source AI tooling
• ▹champion MLOps best practices: model versioning, experiment tracking, data validation, automated retraining
• ▹set up observability, monitoring and alerting for infrastructure and models
• ▹maintain open-source AI tooling hosted at Mollie (LiteLLM, LibreChat)

Requirements

• ▹1+ year deploying and maintaining ML models in production
• ▹good understanding of MLOps principles
• ▹strong hands-on Python skills, proficiency with scikit-learn, pandas, NumPy, XGBoost, LightGBM, MLflow
• ▹familiarity with a major cloud platform, preferably GCP
• ▹experience with containerization (Docker), Kubernetes/Kubeflow a plus
• ▹strong context-switching ability with attention to detail
• ▹familiarity with IaC tools such as Terraform is a plus
• ▹experience building CI/CD pipelines for ML workflows

Soft skills

About the company

Mollie's ML Platform team sits within the broader Data Domain, distributed across Amsterdam and Lisbon in a hybrid/remote setup.