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Senior Machine Learning Engineer - AML Tech

Amsterdam

Pay
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Work setup
Unconfirmed
Employment
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Ensuring a smooth and enjoyable candidate experience is critical for us. We aim to get back to you regarding your application within 5 business days. Our interview process tends to take about 4 weeks to complete, but may fluctuate depending on the role. Learn more about our hiring process here. Don’t be afraid to let us know if you need more flexibility. 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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What you’ll work on

Full posting
  • Develop and maintain production ML pipelines for data ingestion, training, validation, and deployment

  • Upgrade a rules-heavy detection system into a modern automated AI/ML engine

  • Work with data engineers and analysts to build fintech models

  • Keep models working worldwide with operations and compliance teams

  • Solve hard problems such as extreme class imbalance and incomplete ground truth

From the employer’s posting
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

What you’ll bring

All qualifications

Core experience

  • You have 7+ years of experience as an engineer working in the machine learning domain;
  • 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 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
Qualification wording
You have 7+ years of experience as an engineer working in the machine learning domain;
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 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

Tools in this posting

  • Python
  • SQL
  • Docker
  • Grafana
  • MLflow
  • Spark
  • Trino
  • Airflow
  • Lightgbm
  • pandas
  • PySpark
  • PyTorch
  • TensorFlow
  • Xgboost
Source — Tool mentions in context
- 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 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 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;
Nice to Have: - Deep PySpark expertise - Finance domain experience

Posting record

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Live
First seen by us
Oct 16, 2026 · 2d ago
Recorded sightings
2
Last seen by us
Oct 17, 2026

These dates show when we found the listing. Check the employer’s website to confirm it is still accepting applications.

Job description

View original posting ↗

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, 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

Our Diversity, Equity and Inclusion commitments

Our unique approach is a product of our diverse perspectives. This diversity of backgrounds and cultures is essential in helping us maintain our momentum. Our business and technical challenges are unique, and we need as many different voices as possible to join us in solving them - voices like yours. No matter who you are or where you’re from, we welcome you to be your true self at Adyen. 

Studies show that women and members of underrepresented communities apply for jobs only if they meet 100% of the qualifications. Does this sound like you? If so, Adyen encourages you to reconsider and apply. We look forward to your application!

What’s next?

Ensuring a smooth and enjoyable candidate experience is critical for us. We aim to get back to you regarding your application within 5 business days. Our interview process tends to take about 4 weeks to complete, but may fluctuate depending on the role. Learn more about our hiring process here. Don’t be afraid to let us know if you need more flexibility.

This is a full-time position based in our Amsterdam office, and it requires relocation if you are currently living outside of the Netherlands.

Your next step

  • Have your CV and examples of relevant work ready.
  • Check the listed location, eligibility and core experience before starting.
  • Ask the employer about the salary range before committing time to the process.

Complete your application on job-boards.greenhouse.io. The employer’s form will show what is required.

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Pay

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Location & working pattern

Amsterdam

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:
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