What this interview will probe
Builds backend systems that defend Stripe and its users against AI-enabled abuse, integrating model-driven detection into payment and account flows while keeping latency and reliability within Stripe's bars. Works at the intersection of security engineering and applied ML across high-volume services. A technical interview would probe secure system design for adversarial settings, tradeoffs of deploying ML in a latency-sensitive request path, and reasoning about evasion, false positives, and abuse-detection feedback loops.
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