Machine Learning Engineer

Adyen's Anti-money Laundering
Amsterdam, Netherlands
1 day ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
5 years minimum
Working hours
Regular working hours
Job source

Tech stack

Airflow Batch Processing Big Data Information Engineering Distributed Systems Fraud Prevention and Detection Python (Programming Language) Machine Learning Elearning Tensorflow Prometheus Software Engineering
+17 more
SQL Databases Data Streaming Unstructured Data Supervised Learning Feature Store Data Ingestion Pytorch Grafana Apache Spark Pandas Core Data Kubernetes Xgboost Machine Learning Operations Feature Extraction GXP Docker

Job description

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

Requirements

  • 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’

About the company

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., 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.

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