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Adyen

Processes payments online and in stores

Senior Machine Learning Engineer

Applied Machine LearningUpdated on Nov 11
Full-timeAmsterdam, NetherlandsNo salary listed

About the Job

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 PySpark, Trino SQL, TensorFlow, PyTorch, XGBoost, LightGBM, Pandas, MLflow or similar MLOps frameworks, and Airflow.
  • You have knowledge or experience of working with machine learning infrastructure components with tools such as Kubernetes, Docker, Airflow, Argo Workflows, Prometheus, and 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.

Responsibilities

  • Develop and maintain production machine learning pipelines for data ingestion, training, validation, and deployment. Examples of machine learning domains include online learning algorithms to pick the best optimization decision in a changing environment, clustering algorithms to group customers and 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 systems, and real-time anomaly detection based on time-series modeling.
  • Identify and fix performance bottlenecks in machine learning training and inference, including memory consumption, online latency, and training time.
  • Collaborate with software engineers to integrate machine learning 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 priorities for future tools.
  • Support and encourage good engineering practices on product machine learning teams.

Desired Qualifications

  • You have experience with distributed GPU compute environments.
  • You have experience working with a machine learning feature store.

About the Company

Adyen

Processes payments online and in stores

Adyen processes payments for businesses selling online, through mobile apps and in physical stores, with one platform connecting checkout, fraud checks and settlement. Its unified commerce tools connect sales across channels so merchants track transactions and customer activity together. The platform also supports business accounts, card issuing and payouts for software platforms that embed financial services for their users. Merchants integrate its software into their checkout or sales systems and pay a processing fee plus fees based on the payment method, while additional products carry their own charges. Adyen was founded in 2006 and is headquartered in Amsterdam, the Netherlands.

Company size
5,001-10,000
Company stage
IPO
Headquarters
Amsterdam, Netherlands
Founded
2006

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