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Adyen is seeking a Senior Machine Learning Engineer to join its Anti-Money Laundering (AML) team in Amsterdam. The AML team processes over 800 billion euros in transaction volume (H1 2026) to detect complex financial crime and manage customer risks. The team currently operates a hybrid stack of business rules and machine learning models, with a strategic mission to transition from a rules-heavy system to a modern, model-first detection engine.
In this role, you will develop and maintain production ML pipelines for data ingestion, training, validation, and deployment. You will help upgrade the existing rules-heavy system to a modern automated AI/ML engine, collaborating closely with data engineers and data analysts to build best-in-class fintech models. You will also work with operations and compliance teams to ensure models operate reliably worldwide, tackle difficult technical challenges such as extreme class imbalance and incomplete ground truth, and support good engineering practices across the team.
You will proactively lead projects from ideation through deployment, work with diverse stakeholders, and communicate complex outcomes clearly to audiences with varying technical backgrounds. The role emphasizes an experimental mindset with a launch-fast-and-iterate mentality.
REQUIREMENTS:
- 7+ years of experience as an engineer in the machine learning domain
- Strong Python programming skills
- Experience with the full machine learning model lifecycle in production environments
- Experience leveraging big data to create pipelines for model data feeds
- Strong understanding of software engineering practices, data engineering, and MLOps principles
- Knowledge of data science, statistics, and machine learning techniques
- Strong familiarity with standard Python data science tools: (py)spark, (Trino) SQL, TensorFlow, PyTorch, XGBoost/LightGBM, Pandas, MLFlow or similar MLOps frameworks, and Airflow
- Knowledge/experience with ML infrastructure components: Kubernetes, Docker, Airflow, Argo Workflows, Prometheus, Grafana
NICE TO HAVE:
- Deep PySpark expertise
- Finance domain experience
- Experience working with extremely unbalanced data
- Production LLM experience
