Senior ML Engineer, Fraud & Risk

Latitude; Seattle (WA); Ibrido; USD 192.000 - 318.000; Tempo pieno

Descrizione del lavoro

Stripe is seeking a Machine Learning lead to own major ML systems from problem definition to production and to strengthen protections against fraud across the global network. You will design features, build low-latency models, and mentor engineers while collaborating with risk, product, and engineering teams.

You will drive 0→1 innovations and scalable ML infrastructure to support Radar’s evolving threat landscape, ensuring reliability and impact at Stripe scale, with a strong focus on

Competenze

• 5+ years of experience developing, evaluating, and deploying machine learning models in a production environment.
• 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 code for production ML applications.
• Experience designing and operating production ML systems, including data pipelines, distributed training, low-latency inference, deployment, or monitoring.
• Experience mentoring engineers or technically leading projects with multiple contributors.
• Ability to investigate ambiguous problems, reason from data, and choose pragmatic technical approaches.
• Ability to communicate technical ideas and results clearly and collaborate across disciplines.

Mansioni

• 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.

Conoscenze

ML production

Project leadership

Statistics

Software engineering

Low-latency inference

Mentoring

Cross-team communication

Descrizione del lavoro

Stripe is seeking a Machine Learning lead to own major ML systems from problem definition to production and to strengthen protections against fraud across the global network. You will design features, build low-latency models, and mentor engineers while collaborating with risk, product, and engineering teams.

You will drive 0→1 innovations and scalable ML infrastructure to support Radar’s evolving threat landscape, ensuring reliability and impact at Stripe scale, with a strong focus on