ML Engineering Manager, Payment Intelligence
Stripe
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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 Payment Intelligence organization optimizes each of the billions of dollars of transactions processed by Stripe annually on behalf of our users, maximizing successful transactions while minimizing payment costs and fraud. We own products like Radar end-to-end, developing machine learning models, building fast and scalable services and creating intuitive user experiences. We serve real-time predictions as part of Stripe’s payment infrastructure and architect controls that leverage ML to optimally manage users’ business.
What you’ll do
We are looking for an engineering manager to lead and grow a strong team of machine learning engineers that design, build, deploy, and operate ML-powered services that scale globally with Stripe. You will partner with many functions, especially data science (DS), as you lead Stripe's most critical payment decisioning infrastructure.
Responsibilities
- Set the vision, goals, & strategy for the team based on company objectives
- Lead by example in high-growth, high-impact, ambiguous environments
- Build machine learning systems and pipelines for training, shipping, and operating machine learning models
- Improve existing machine learning models via developing new ML features, which has been the primary path for improving performance
- Collaborate and execute projects cross-functionally with the data science, product, infrastructure, and risk teams
- Ensure engineering outcomes meet or exceed established standards of excellence in code quality, system design, and scalability
- Recruit, hire, scale, and develop an amazing team of engineers
- Accelerate the delivery of models to production by leading continuous engineering improvements and investments in our MLOps infrastructure
- Propose and implement innovative product ideas to reduce costs and combat fraud at Stripe
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 direct engineering management experience
- 2+ year of experience working within a team responsible for developing, managing, and improving ML models or ML infrastructure
Preferred qualifications
- Proven track record of building and deploying machine learning models or systems that have effectively solved critical business problems
- Experience managing teams that leverage real-time, distributed data processing
- Experience managing teams that leverage batch processing pipelines
- Experience building sustainable operations for managing many ML models, including CI/CD, auto-training, auto-deployment, and continuous model refreshes
- Experience managing teams that owned many diverse ML models
- Experience in adversarial domains like Fraud, Trust, or Safety
- Past experience operating under team goal-setting frameworks such as OKRs
This role is available either in an office or a remote location (typically, 35+ miles or 56+ km from a Stripe office).
Office-assigned Stripes spend at least 50% of the time in a given month in their local office or with users. This hits a balance between bringing people together for in-person collaboration and learning from each other, while supporting flexibility about how to do this in a way that makes sense for individuals and their teams.
A remote location, in most cases, 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. We encourage you to apply for roles that match the location where you currently or plan to live.
The annual US base salary range for this role is $224,300 - $336,500. 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. This salary range may be inclusive of several career levels at Stripe and will be narrowed during the interview process based on a number of factors, including the candidate’s experience, qualifications, and location. Applicants interested in this role and who are not located in the US may request the annual salary range for their location during the interview process.
Additional benefits for this role may include: equity, company bonus or sales commissions/bonuses; 401(k) plan; medical, dental, and vision benefits; and wellness stipends.
Office locations
Seattle, New York, or South San Francisco HQ
Remote locations
Remote in United States
Team
New Financial Products
Job type
Full time
This job is no longer accepting applications
See open jobs at Stripe.See open jobs similar to "ML Engineering Manager, Payment Intelligence" Glynn Capital.