Machine Learning Engineer
Description For Machine Learning Engineer
Mollie is seeking a Machine Learning Engineer to join their growing team of Data Scientists and Machine Learning Engineers. This role is part of a central entity that develops and deploys machine learning capabilities across various domains, including Monitoring (Risk & Fraud), Payments, Merchant Experience, Financial Services, and Go-to-Market.
The successful candidate will be hands-on, spending most of their time coding in Python and Terraform. They will collaborate closely with ML Engineers, Data Scientists, and various engineers across Mollie. Key responsibilities include contributing to the design, development, and maintenance of a scalable, low-latency cloud ML Platform and services, deploying ML models to production, and promoting best practices in MLOps.
The ideal candidate should have 1-3 years of experience as an ML Engineer, advanced software engineering skills with a focus on Python, familiarity with cloud ML platforms (preferably Google Cloud's Vertex AI), and experience with containers and orchestration tools. They should also be proficient with Terraform, comfortable with Linux and Git, and knowledgeable about the Model Development Lifecycle and common DS libraries.
This position offers the opportunity to work on cutting-edge projects, including a multi-cloud ML Platform and MollieGPT, an in-house GenAI solution. The role is based in Mollie's Lisbon Hub but is part of a geographically distributed team that embraces remote and hybrid collaboration.
Join Mollie to be at the forefront of machine learning in the fintech industry, working with a diverse, collaborative team and contributing to innovative solutions that impact various aspects of the business.
Responsibilities For Machine Learning Engineer
- Collaborate closely with ML Engineers, Data Scientists, and various engineers across Mollie
- Contribute to the design, development, and maintenance of our scalable, low-latency cloud ML Platform and services
- Deploy ML models to production in partnership with Data Scientists
- Promote and implement best practices and standards in MLOps
- Document MLOps workflows and architecture, ensuring compatibility with other systems at Mollie, including compliance with security standards (e.g., threat modeling)
Requirements For Machine Learning Engineer
- 1-3 years of proven experience as an ML Engineer (or similar role), including developing and maintaining ML Platforms and Model Pipelines in production environments
- Advanced software engineering skills with a passion for coding in Python
- Familiarity with at least one major cloud ML platform, preferably Google Cloud's Vertex AI
- Experience with containers and container orchestration, such as Docker, Kubernetes, and Kubeflow
- Proficiency with Terraform or similar infrastructure-as-code (IaC) tools
- Comfort with using a Linux shell and Git for version control
- Knowledge of the Model Development Lifecycle and common DS libraries, such as scikit-learn, pandas, shap, feature-engine, xgboost (or lgbm), and MLflow
- Attention to detail with the ability to quickly shift priorities when required
- Strong presentation skills and the ability to communicate effectively with diverse audiences
- Enjoy working collaboratively in a cross-functional and distributed team environment
- Comfort with Agile methodologies, such as Scrum, Kanban, or similar frameworks
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