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Adyen

Senior Machine Learning Engineer

Adyen is hiring a Senior Machine Learning Engineer in Amsterdam, Netherlands. Level rates it ; you can apply on Level.

AI in this role

pytorchtensorflowxgboostmlflow
ml-ops

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.

How we rate this

Senior Machine Learning Engineer at Adyen rates 93 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.

Classification

Builds AI. The job is building AI systems.

  1. ●●●● Builds AI80 to 100
  2. ●●●○ Works on AI60 to 79
  3. ●●○○ Uses AI40 to 59
  4. ●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Open the description and count.

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

ML OpsPyTorchTensorFlowXGBoostMlflow

Also common in machine learning engineer jobs at this level

Pay

Typical machine learning engineer job
$198k

This posting doesn't list pay. Use the typical machine learning engineer figure when pay comes up. See machine learning engineer jobs

Questions you could be asked

  1. How do you monitor a model once it's live, and how do you know it needs retraining?
  2. Walk me through how you've used PyTorch in your day-to-day work.
  3. What are the limits of TensorFlow that you've run into, and how did you work around them?
  4. What's a project where you used XGBoost hands-on?
  5. Walk me through how you've used Mlflow in your day-to-day work.

Adapt your resume

  • List these exact terms on your resume: ML Ops, PyTorch, TensorFlow, XGBoost, and Mlflow. An applicant tracking system matches the wording, not the idea.
  • Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
  • Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.

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