Machine Learning Engineering Manager

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

Benefits

• 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