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Staff Applied Machine Learning Engineer - Fraud & Abuse

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about 3 hours ago

Base Salary

$277k - $415k/yr

Responsibilities

  • Build and operate real-time and batch ML decisioning systems for fraud and abuse prevention.
  • Integrate various signals into low-latency model serving and decision APIs.
  • Own the production lifecycle for risk decisions, including monitoring and incident response.
  • Develop feedback loops and AI-assisted workflows for investigation and learning.
  • Collaborate with modelers, analysts, and product teams to balance fraud losses and customer access.
  • Create reusable decision capabilities for internal tools and workflows.

Requirements

  • 12+ years of experience in building and operating production software and ML systems.
  • Deep expertise in fraud/risk domains such as payment fraud and identity integrity.
  • Strong production ML judgment across various aspects of model deployment.
  • Sound judgment regarding false-positive tradeoffs and customer harm.
  • Experience with AI-assisted engineering tools for high-stakes systems.

Benefits

  • Remote work options available.
  • Comprehensive medical insurance.
  • Flexible time off policies.
  • Retirement savings plans.
  • Modern family planning support.

Tech Stack

Categories

AI & MLData Science