Requirements

• 1+ year of experience deploying and maintaining ML models in production
• Good understanding of MLOps principles
• Strong hands-on Python programming skills
• Familiarity with a major cloud platform, preferably GCP
• Experience with containerization (Docker) and container orchestration tools
• Strong context-switching ability with sharp attention to detail
• Preferably familiarity with infrastructure-as-code tools such as Terraform
• Experience building and maintaining CI/CD pipelines for ML workflows

What you'll be doing

• Collaborate closely with ML Platform Engineers, Machine Learning Scientists, and engineers
• Deploy and operationalize ML models to production
• Enhance and maintain our cloud-based ML Platform on GCP
• Build and maintain CI/CD pipelines for ML model training and inference
• Deploy, manage, and scale model serving endpoints on Kubernetes
• Assist in extending, developing, and hosting custom and open-source AI tooling
• Champion MLOps best practices
• Ensure platform reliability by setting up observability, monitoring, and alerting
• Maintain and enhance open-source AI tooling hosted at Mollie

Grow your way

• Regular feedback and performance reviews
• Fair and transparent salary reviews
• Opportunities to develop skills, explore new challenges, and shape your career

Perks and Benefits

• Support and opportunities for growth
• Promotion and career advancement possibilities
• Cutting-edge projects in the finance industry