About this role
This is Adyen
At Adyen, we’re engineered for ambition. We empower our teams with the culture and support they need to own their careers. The people of Adyen are motivated problem-solvers who tackle unique technical challenges at scale, delivering innovative and ethical solutions to help businesses achieve their ambitions faster.
For our teams, we create an environment with opportunities for our people to succeed, backed by the culture and support to ensure they are enabled to truly own their careers. We are motivated individuals who tackle unique technical challenges at scale and solve them as a team. Together, we deliver innovative and ethical solutions that help businesses achieve their ambitions faster.
Senior Machine Learning Engineer
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.
In this role, you will:
• 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
Who You Are:
• 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,