Machine Learning Engineer, Link

Job summary

Responsibilities

As a machine learning engineer on Link Fraud and Auth, you’ll build and operate models and risk decisioning systems that protect Link while helping more legitimate payments succeed. You’ll work across the full machine learning lifecycle, from analyzing fraud patterns and identifying opportunities…

• Build, train, evaluate, deploy, and own machine learning models that detect fraud and abuse across Link.
• Use large-scale datasets to investigate emerging threats, develop hypotheses, and identify opportunities to improve payment performance.
• Develop pragmatic machine learning solutions, including tree-based models and other approaches suited to real-time risk decisioning.
• Design data pipelines, features, evaluation methods, experiments, and monitoring systems that support reliable production models.
• Build and improve risk decisioning systems that integrate with other parts of Stripe’s payments stack.

What they're looking for

• 6+ years of industry experience building and shipping machine learning models in production.
• Strong programming skills in Python and experience with common data and machine learning tools, such as SQL, Spark, and XGBoost.
• Strong knowledge of production machine learning systems, including data pipelines, feature development, model evaluation, deployment, monitoring, and iteration.
• Experience working with large and complex datasets and applying data analysis, statistics, and experimentation fundamentals.
• Demonstrated ability to take an open-ended business problem, determine where machine learning can help, and own the solution through production.

Tech stack

• Python
• SQL
• Spark