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 team in Amsterdam, someone with experience of building and operating robust machine learning systems at scale in production environments. You will be responsible for designing, productionizing and maintaining machine learning services that power data products at Adyen.
Teams Currently Hiring:
Optimise:
Optimize Intelligence at Adyen is a specialized team of Machine Learning Scientists and Data Analysts focused on maximizing transaction success, minimizing transaction costs, and driving payment performance at a global scale. We build and scale advanced ML/DL solutions that operate over massive, complex decision spaces, determining the optimal path for every single transaction in real time. Our systems evaluate high-dimensional data streams to dynamically select the optimal authentication methods, apply smart payment message optimizations, and orchestrate intelligent transaction routing. Our models live-score millions of daily transactions, balancing coupled cost and performance objectives simultaneously.
If you are passionate about solving intricate combinatorial challenges and pushing the boundaries of adaptive decision-making systems, join us in shaping the future of payments.
Identity and Verification Decisioning:
This is an opportunity to help define how Adyen makes identity decisions at global scale.
The team sits at the intersection of machine learning, distributed systems, fraud prevention, compliance, and customer experience. Rather than optimizing isolated models, you'll help build the intelligence that determines how millions of businesses and individuals are verified throughout their lifecycle.
You'll join a newly formed engineering team, giving you significant influence over the technical direction, architecture, and ML strategy from an early stage. Your work will directly impact fraud prevention, regulatory compliance, operational efficiency, and customer onboarding experience.
Payments Core Data - Disputes:
Adyen is building a dispute intelligence function. The team will be building ML and AI applications to make our dispute product more intelligent. We’re looking for someone with an optimization mindset, looking for an opportunity which allows for continuous experimentation and improvement by enriching the algorithms context (structured and unstructured data).
The challenge for the person refers to a greenfield opportunity, allowing for Disputes Machine Learning and AI use cases to be built from the ground up. You’ll be working side-by-side with both the Data Engineers and Machine Learning Scientists with respect to disputes data, and with the disputes engineering team who are owning the dispute product as a whole.
AML Tech:
Adyen's Anti-Money Laundering team processes massive transaction volume 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.
As a Senior Machine Learning Engineer, you'll play a critical role in this evolution. You will architect scalable batch processing pipelines, tackle hard technical challenges like extreme class imbalance and incomplete ground truth, and drive production ML systems that will make financial world safer for everyone.
In this role, you will:
- Develop and maintain production ML pipelines for data ingestion, training, validation, and deployment. Examples ML domains are: on-line learning algorithms to pick the best optimization decision in a changing environment, clustering algorithms to group customers/shoppers, supervised and semi-supervised learning methods for inference on risk patterns or graph analysis, representation learning for behavior prediction and monitoring, Anti-Money Laundering (AML) systems and real-time anomaly detection based on time-series modeling;
- Identify and fix performance bottlenecks in ML training and inference (memory consumption, online latency, training time etc.);
- Collaborate with software engineers to integrate ML solutions into products and services;
- Collaborate with data scientists to transition research prototypes into scalable solutions;
- Collaborate with MLOps and platform teams to integrate effectively with current tools, and shape priority for future tools;
- Support and encourage good engineering practices on product ML teams;
Who You Are:
- You have 5+ 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:
- You have experience with distributed GPU compute environments
- You have experience working with a Machine Learning ‘Feature Store’
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
- 5+ 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, 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, and Airflow
- Experience with ML infrastructure tools such as Kubernetes, Docker, Airflow, Argo Workflows, Prometheus, and Grafana
- Experimental mindset with a launch-fast and iterate approach
- Ability to lead projects from ideation through deployment and communicate with diverse stakeholders
- Experience with distributed GPU compute environments
- Experience working with a machine learning feature store
Adyen Compensation & Benefits Highlights
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Leave & Time Off Breadth — Feedback suggests time off is generous in the U.S., with unlimited PTO that employees actually use for substantial vacations.
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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.
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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
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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Adyen Teams
Adyen Offices
Hybrid Workspace
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.





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