Engineering Manager, Machine Learning - Credit Risk
Stripe Open · verified Oct 22, 2026 At a glance
Manager-level Machine Learning Engineering role at Stripe. N/A.
Pay not stated Machine Learning Engineering salary
aimlroles summary, based on the employer's posting.
What you'll do
- Set the machine-learning plan for finding and reducing credit risk, and own results for losses, profitability, detection quality and user experience
- Guide teams building dependable models, services and decision systems for credit-risk decisions
- Turn machine-learning advances into practical capabilities tied to business goals
- Work with product, data science, credit strategy, operations and engineering partners to choose priorities and deliver shared programs
- Hire and develop machine-learning engineers, improve technical practices and contribute to engineering leadership
What you bring
- At least three years managing engineers responsible for production machine-learning systems
- You have applied machine learning to complex problems and led delivery of models and their supporting systems
- You have set strategy and coordinated across technical, data, operations and business teams to achieve measurable outcomes
- You have recruited, managed and developed engineers in a fast-moving setting with significant autonomy
Who this fits
This role suits an engineering manager who can connect machine-learning delivery to credit-risk outcomes and balance loss prevention with user experience. You’ll lead and develop engineers while setting direction and working across functions.
From the employer
Engineering Manager, Machine Learning Credit Risk
Who we are
About 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. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone’s reach while doing the most important work of your career.
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.
Responsibilities
- 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
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.
Minimum requirements
- 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
Preferred qualifications
- 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