Engineering Manager, Machine Learning - Credit Risk

Stripe, Inc.; United States; Remote; USD 180,000 - 240,000; Full time

Job summary

Stripe, Inc. is seeking an Engineering Manager to lead a machine learning team focused on credit risk for a financial products platform.

The role combines technical direction, people management, and cross-functional program delivery at scale to surface risky accounts, reduce credit losses, and ensure a reliable experience for legitimate users. The successful candidate will set strategy for ML-driven risk detection, own outcomes related to losses and profitability, and recruit top ML engineers

Qualifications

• 3+ years leading engineers on production ML systems.

Responsibilities

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

Job description

Role overview

An engineering manager is needed to lead a machine learning team focused on credit risk for a financial products platform. The team builds models and decision systems that surface risky accounts, reduce credit losses, and preserve a reliable experience for legitimate users. This is a senior leadership role that combines technical direction, people management, and cross-functional program delivery at scale.

Responsibilities

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

Requirements

• 3+ years of experience leading engineers who build and operate production machine learning systems
• Hands-on experience applying ML to complex real-world problems and leading the technical delivery of models and supporting infrastructure
• Track record of setting strategy and delivering measurable outcomes with product, data science, operations, and business partners
• Experience recruiting, managing, and developing engineers in a fast-moving environment with significant autonomy

Nice to have

• Background in 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 ML 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