Adyen

Machine learning engineer in AML

In short

Senior Machine Learning Engineer role on Adyen's Anti-Money Laundering team in Amsterdam, building and operating production ML systems that detect financial crime across massive transaction volumes. The team is moving from a rules-heavy detection system to a modern model-first ML engine, requiring strong Python, big data pipelines, and MLOps expertise. Candidates need 7+ years of ML engineering experience and familiarity with tools like PySpark, TensorFlow, PyTorch, Airflow, and Kubernetes. The role is hybrid, full-time, and requires relocation to the Netherlands if not already based there.

About the role
Adyen is looking for a Senior Machine Learning Engineer to join our Anti-Money Laundering team in Amsterdam, someone with experience of building and operating robust machine learning systems at scale in production environments. The Anti-Money Laundering team processes a massive transaction volume (over 800B euro in H1 2026) to detect complex financial crime and cover a wide range of customer risks. We currently run a hybrid stack of business rules and machine learning models, with a clear mission to systematically reduce our dependence on static rules and transition to a modern, model-first detection engine.
Responsibilities
•Develop and maintain production ML pipelines for data ingestion, training, validation, and deployment
•Help us upgrade an existing rules-heavy system to a modern automated AI/ML engine
•Collaborate with data engineers and data analysts to develop best in class Fintech models
•Collaborate with operations and compliance teams to ensure Adyen's models operate worldwide without a hitch
•Tackle difficult technical challenges like extreme class imbalance and incomplete ground truth
•Support and encourage good engineering practices
Requirements
•You have 7+ years of experience as an engineer working in the machine learning domain
•You are a strong Python programmer
•You have experience with the full machine learning model lifecycle in production flows
•You have experience leveraging big data to create the pipelines needed to feed the models with appropriate data
•You have a strong understanding of good software engineering practices as well as data engineering and MLOps principles
•You have knowledge of data science, statistics and machine learning techniques
•You have strong familiarity with the standard data science toolkit in python, such as (py)spark, (Trino) SQL, Tensorflow, PyTorch, XGBoost/LightGBM, Pandas, MLFlow or similar MLOps frameworks, and Airflow
•You have knowledge/experience of working with ML infrastructure components with tools such as k8s, docker, airflow, argo-workflows, prometheus, grafana
•You have an experimental mindset with a launch fast and iterate mentality
•You proactively take the lead in projects, from ideation to deployment
•You have experience working with a wide range of stakeholders and can clearly communicate complex outcomes over a wide range of audiences
Nice to have
•Deep PySpark expertise
•Finance domain experience
•Worked with extremely unbalanced data
•Production LLM experience
Conditions
This is a full-time position based in our Amsterdam office, and it requires relocation if you are currently living outside of the Netherlands.

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