Senior Real-Time Fraud ML Engineer

Fdetimes; Seattle (WA); Sur place; USD 210 000 - 270 000; Plein temps

Résumé du poste

Stripe’s Radar ML team seeks a seasoned Machine Learning Engineer to own major ML systems end-to-end, from problem framing to production deployment and monitoring. You’ll design features for fraud detection, ship scalable models, and collaborate with cross-functional partners to advance Radar protections at Stripe scale.

You will lead architecture decisions, drive experimentation rigor, and mentor engineers while delivering high-impact, reliable ML solutions in a fast-paced payments environment.

Qualifications

• 5+ years of production ML experience.
• Proven track record leading ML projects end-to-end.
• Strong foundations in ML, statistics, evaluation, and experimentation.
• Proficient in production-grade software engineering.
• Experience designing and operating large-scale, low-latency ML systems.
• Experience mentoring engineers and leading teams.
• Ability to analyze ambiguous problems using data.
• Clear communicator across engineering, product, and risk teams.

Responsabilités

• Lead the design and delivery of ML projects end to end, from framing the problem and sizing the opportunity through deployment, monitoring, and iteration.
• Build, train, evaluate, and deploy models that detect fraud and abuse across Stripe’s global network, and own the production systems they run on.
• Investigate emerging fraud and abuse patterns, decide where ML can have the most impact, and quickly turn those insights into shipped protections.
• Design features, datasets, and evaluation strategies for noisy, delayed, and adversarial environments, and set the bar for experimental rigor.
• Make sound architecture and modeling tradeoffs between model quality, legitimate-user impact, latency, reliability, and operational cost.
• Be the go-to expert for the systems you own: lead incident response for model regressions, reduce operational toil, and make your systems easy for others to build on.
• Partner with engineering, product, data science, risk experts, and leading Stripe users to turn modeling improvements into differentiated Radar products.
• Turn recurring problems into reusable components, tools, and AI-assisted workflows that speed up the whole team.
• Mentor engineers, give thoughtful design and code reviews, and help new teammates ramp up quickly.

Connaissances

ML in production

ML project leadership

ML foundations

Production-grade coding

Production ML systems

Mentoring

Analytical thinking

Communication

Description du poste

Stripe’s Radar ML team seeks a seasoned Machine Learning Engineer to own major ML systems end-to-end, from problem framing to production deployment and monitoring. You’ll design features for fraud detection, ship scalable models, and collaborate with cross-functional partners to advance Radar protections at Stripe scale.

You will lead architecture decisions, drive experimentation rigor, and mentor engineers while delivering high-impact, reliable ML solutions in a fast-paced payments environment.