Engineering Manager, Machine Learning Credit RiskWho we areAbout Stripe Stripe is a financial infrastructure platform for businesses. Millions of companies from the world's largest enterprises to the most ambitious startups use Stripe to accept payments, grow their revenue, and accelerate new business opportunities.

About the team 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. Our team consists of machine learning engineers who build models and systems used across Stripe’s credit-risk products.

We work closely with partners in Product, Data Science, Credit Strategy, Operations, and other engineering teams. Together, we help stakeholders make informed decisions and support sustainable growth wherever credit risk affects Stripe’s products. What you’ll do We’re looking for an engineering manager to lead the Credit Risk team and shape how Stripe uses machine learning to manage credit risk at scale.

You’ll set the team’s technical and product direction, connect advances in machine learning to measurable business outcomes, and help engineers deliver reliable systems that balance loss prevention with the user experience. You’ll work across engineering, product, data science, and risk to identify the highest-impact opportunities and turn them into a focused roadmap. You’ll also hire and develop engineers, strengthen the team’s technical practices, and contribute to machine learning and engineering leadership across Stripe.





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 If you meet these requirements, you are encouraged to apply. The preferred qualifications are a bonus, not a requirement. 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 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 Hybrid work at Stripe This role is available either in an office or a remote location (35+ miles or 56+ km from a Stripe office). In-office expectations Office-assigned Stripes spend at least 50% of the time in a given month in their local office or with users.

Working remotely at Stripe A remote location is defined as being 35 miles (56 kilometers) or more from one of our offices. While you would be welcome to come into the office for team/business meetings, on‑sites, meet‑ups, and events, our expectation is you would regularly work from home rather than a Stripe office. Stripe does not cover the cost of relocating to a remote location.

For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role.

Additional benefits for this role may include: equity, company bonus or sales commissions/bonuses; medical, dental, and vision advantages; Please find our California applicant personal information notice here. Team Risk & Financial Crimes Office locations Toronto, Atlanta, Chicago, New York, Seattle, South San Francisco HQ Remote locations Remote in Canada, Remote in United States Employment type Full time #

📌 Engineering Manager, Machine Learning - Credit Risk (Toronto)
🏢 Stripe
📍 Toronto