Senior Machine Learning Engineer

Join Adyen, a leading global payment company, as a Senior Machine Learning Engineer. In this role, you will design, productionize, and maintain machine learning services that power data products at Adyen. You will work with various teams focused on optimizing transaction success, identity verification, dispute intelligence, and anti-money laundering. You will have the opportunity to shape the technical direction, architecture, and ML strategy from an early stage.

Design, productionize, and maintain machine learning services that power data products at Adyen.

Collaborate with software engineers, data scientists, and MLOps teams to integrate ML solutions into products and services.

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!

Responsibilities

• Identify and fix performance bottlenecks in ML training and inference, and support good engineering practices on product ML teams.

Requirements

• You have knowledge/experience of working with ML infrastructure components with tools such as k8s, docker, airflow, argo-workflows, prometheus, grafana
• You have experience with the full machine learning model lifecycle in production flows
• 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
• You have 5+ years of experience as an engineer working in the machine learning domain
• 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 a strong understanding of good software engineering practices as well as data engineering and MLOps principles

You are a strong Python programmer

• You have an experimental mindset with a launch fast and iterate mentality
• You have experience leveraging big data to create the pipelines needed to feed the models with appropriate data
• You have knowledge of data science, statistics and machine learning techniques
• You have experience with distributed GPU compute environments
• You have experience working with a Machine Learning ‘Feature Store’