Who you are

- We’re looking for someone who meets the minimum requirements to be considered for the role. 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 recruiting, managing, and developing engineers in a fast-moving environment with significant autonomy

- 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 involves

- 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

- 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

Perks

- Gym membership
- Food provided in the office

- Unlimited paid time off policy

- Work from home opportunities
- Comprehensive mental, physical and medical health plans

- Fertility benefits and parental leave

📌 Machine Learning Engineering Manager (Toronto)
🏢 Stripe
📍 Toronto