Engineering Manager, Machine Learning - Credit Risk

Stripe · N/A · 8535 Risk Credit & Fraud · listed September 15, 2026

The shape of it

Seniority
Manager
Experience asked
3+ years
Where
Not stated
Requirements listed
4
Length
553 words

In the posting’s own words

The Credit Risk team develops intelligent systems that help Stripe identify high-risk accounts, minimize credit losses, and improve profitability. Credit risk is a complex machine learning problem that requires us to distinguish emerging risk from healthy business activity while giving legitimate users a clear and reliable experience.

What it asks for · 4

  • 3+ years of experience managing engineers who build and operate production machine learning systems
  • Experience applying machine learning to complex, real-world problems and leading the technical delivery of models and supporting systems
  • Experience setting strategy and working across engineering, product, data science, operations, and business teams to deliver measurable outcomes
  • Experience recruiting, managing, and developing engineers in a fast-moving environment with significant autonomy

Also a plus

  • Experience with credit risk, fraud detection, financial risk, trust and safety, or another domain involving decisions under uncertainty
  • Experience balancing risk reduction with customer or user experience
  • Experience building machine learning systems that support high-stakes, time-sensitive decisions at scale
  • Experience setting a multi-year technical direction while delivering progress through quarterly plans
  • Experience managing geographically distributed teams

What the job covers

  • Set and execute the strategy for detecting and mitigating credit risk through machine learning
  • Own outcomes related to credit losses, profitability, detection quality, and the user experience
  • Lead the design and delivery of reliable machine learning models, services, and decision systems
  • Translate advances in machine learning into practical capabilities that support the team’s business goals
  • Partner with Product, Data Science, Credit Strategy, Operations, and engineering teams to define priorities and deliver cross-functional programs
  • Recruit, hire, and develop machine learning engineers while building an inclusive and effective team
  • Contribute to broader engineering and machine learning initiatives as a member of Stripe’s engineering management team

Tools and skills named

Models & research
  • Machine learning14×
Product & design
  • User experience3×
  • Roadmap
Operations & finance
  • Recruiting
Ways of working
  • Cross-functional

Words the posting leans on

  • machine learning14×
  • experience13×
  • engineering9×
  • credit risk8×
  • product7×
  • systems7×
  • engineers6×
  • business4×
  • data science4×
  • decisions4×
  • product data4×
  • requirements4×
  • strategy4×
  • technical4×
  • deliver3×
  • develop3×

Counted from the posting after the mission statement and the legal notices are set aside. The ones near the top are the ones a screener is looking for.

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How this page was made

An automated read of a public job posting, fetched September 16, 2026 and last changed by Stripe on September 15, 2026. Every list above is pulled from the posting’s own sentences — nothing rewritten, nothing added, no judgment about the role or the company. Counts and seniority are read off the text by rule, so they can be wrong where the posting is unusual. The original is the only thing that binds. Openings close without warning; check the source before spending an evening on it.