Senior Machine Learning Engineer - AML Tech

Posted Yesterday
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Amsterdam, NLD
Hybrid
Senior level
Fintech • Payments • Financial Services
Meet the financial technology platform helping the world’s leading businesses achieve their ambitions faster.
The Role
Build and operate production machine learning pipelines for Adyen’s anti-money laundering systems. Modernize rules-based detection into an AI/ML engine, develop models using large-scale transaction data, address class imbalance and incomplete labels, and collaborate with data engineering, analytics, operations, and compliance teams. Lead projects from ideation through deployment while promoting strong software engineering, data engineering, and MLOps practices.
Summary Generated by Built In

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.

Skills Required

  • 7+ years of experience as an engineer working in machine learning
  • Strong Python programming skills
  • Experience with the full machine learning model lifecycle in production
  • Experience using big data to build model data pipelines
  • Strong understanding of software engineering practices, data engineering, and MLOps principles
  • Knowledge of data science, statistics, and machine learning techniques
  • Familiarity with Python data science tools including PySpark, Trino SQL, TensorFlow, PyTorch, XGBoost or LightGBM, Pandas, MLflow or similar MLOps frameworks, and Airflow
  • Experience with ML infrastructure tools such as Kubernetes, Docker, Airflow, Argo Workflows, Prometheus, and Grafana
  • Experimental mindset and willingness to iterate quickly
  • Ability to lead projects from ideation through deployment and communicate complex outcomes to diverse stakeholders
  • Deep PySpark expertise
  • Finance domain experience
  • Experience working with extremely unbalanced data
  • Production LLM experience

What the Team is Saying

Bhumika
Blaine
Ayesha
Tulasi
Robbie
Suzanne
Katie
Zachary
Savannah
Sam
Adam
Lindsay
Maxine
Sandeep
Rose
Chris
Harsh
Maxine
Sudhee
Sam
Sandeep
Pragad
Katie
Adam
Edward
Zachary
Sudhee
Adra
Bhumika
Harsh
Christianne
Sarah
Pragad
Ayesha
Savannah
Robbie
Madeline
Gargi
Gargi
Blaine
Zachary
Madeline
Gargi
Bhumika
Harsh
Rose
Katie
Megan
Harsh
João
Rose
Suzanne
Leslie
Harsh
Savannah
Rose
Rose
Catherine Ye
Catherine Ye

Adyen Compensation & Benefits Highlights

  • Leave & Time Off Breadth — Feedback suggests time off is generous in the U.S., with unlimited PTO that employees actually use for substantial vacations.
  • Healthcare Strength — Feedback suggests U.S. health coverage is strong, with substantial employer-paid contributions and coverage that includes dental, vision, and mental-health support.
  • Flexible Benefits — Feedback suggests Adyen+ provides a monthly, flexible contribution employees can direct to needs like childcare, language courses, wellness, or home-office equipment.

Adyen Insights

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The Company
HQ: Amsterdam
4,771 Employees
Year Founded: 2006

What We Do

Adyen (ADYEN:AMS) is the financial technology platform of choice for leading companies. By providing end-to-end payments capabilities, data-driven insights, and financial products in a single global solution, Adyen helps businesses achieve their ambitions faster. With offices around the world, Adyen works with the likes of Meta, Uber, H&M, eBay, and Microsoft.

Why Work With Us

At Adyen, everything we do is engineered for ambition. We started with payments, at a time when providers offered services based on a patchwork of systems built on outdated infrastructure. Ambition demanded more. So we set off to build a financial technology platform for the modern era, entirely in-house, from the ground up.

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Employees engage in a combination of remote and on-site work.

We believe that in-person collaboration is the best route to building genuine connection. We’re an office-first company that offers flexibility when needed. We trust our team to act with autonomy and make good choices.

Typical time on-site: Flexible
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