Machine Learning Engineer, Transaction Risk

📋 Description

• Lead the design and delivery of ML projects end to end, from framing the problem and sizing the
• Build, train, evaluate, and deploy models that detect fraud and abuse across Stripe’s global
• Investigate emerging fraud and abuse patterns, decide where ML can have the most impact, and
• Design features, datasets, and evaluation strategies for noisy, delayed, and adversarial
• Make sound architecture and modeling tradeoffs between model quality, legitimate-user impact
• Be the go-to expert for the systems you own: lead incident response for model regressions, reduce

🎯 Requirements

• 5+ years of experience developing, evaluating, and deploying machine learning models in a
• A track record of leading ML projects from problem definition to production, with measurable impact.
• Deep foundations in machine learning, statistics, model evaluation, and experiment design.
• Strong programming and software-engineering skills, with experience writing tested, maintainable
• Experience designing and operating production ML systems, including several of: large-scale data
• Experience mentoring engineers or technically leading projects with multiple contributors.