The opportunity
At Adyen, we’re engineered for ambition. We empower our teams with the culture and support they need to own their careers.
What you'll do
Customer Risk
Account Risk Engine
Behavioural Fraud
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;
What they're looking for
- 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;
- You have 5+ years of experience as an engineer working in the machine learning domain;
