Real-Time Fraud & Risk ML Engineer

FDE Times; New York (NY); On-site; USD 150,000 - 210,000; Full time

Job summary

Stripe is seeking a Machine Learning Engineer for the Link Fraud and Auth team. You will build and operate models and risk decisioning systems that protect Link while enabling more legitimate payments to succeed.

You’ll cover the full ML lifecycle—from fraud pattern analysis to deployment, monitoring, and improvement of models in production. You will partner with Engineering, Product, and Data Science to form hypotheses, choose practical modeling approaches, and set technical direction.

Qualifications

• 6+ years of industry experience building and shipping ML models in production.
• Strong programming skills in Python and experience with SQL, Spark, and XGBoost.
• Strong knowledge of production ML 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.
• Ability to take open-ended business problems and own the solution through production.
• Good judgment in selecting practical modeling approaches balancing performance, complexity, latency, and business impact.
• Strong collaboration skills across teams to contribute to peers' success.

Responsibilities

• Build, train, evaluate, deploy, and own ML models that detect fraud and abuse across Link.
• Use large-scale datasets to investigate threats, develop hypotheses, and improve payment performance.
• Develop pragmatic ML solutions, including tree-based models and other real-time risk approaches.
• Design data pipelines, features, evaluation methods, experiments, and monitoring systems for production models.
• Build and improve risk decisioning systems that integrate with Stripe’s payments stack.
• Own ambiguous problems from analysis to launch, measurement, and iteration.
• Collaborate with Engineering, Product, Data Science, and Risk teams to turn model improvements into product outcomes.

Skills

Python

SQL

Spark

XGBoost

ML engineering

Job description

Stripe is seeking a Machine Learning Engineer for the Link Fraud and Auth team. You will build and operate models and risk decisioning systems that protect Link while enabling more legitimate payments to succeed.

You’ll cover the full ML lifecycle—from fraud pattern analysis to deployment, monitoring, and improvement of models in production. You will partner with Engineering, Product, and Data Science to form hypotheses, choose practical modeling approaches, and set technical direction.