Engineering Manager, Machine Learning - Credit Risk

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