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Design, prototype, and productionize fraud detection ML models and rules‑based systems, while shaping data architectures and roadmaps in partnership with fraud engineering and data platform teams.
5+ years as a Machine Learning Engineer, Applied Scientist or Data Scientist with strong Python (numpy, pandas, sklearn, PyTorch), SQL, and experience deploying ML models to production; a quantitative degree and ability to use AI‑assist tools.
Effective fraud detection directly protects Ramp’s $200B+ transaction flow, reduces risk for users, and supports the company’s mission to automate spend for millions of businesses.
A high‑agency, fast‑paced builder who thrives in a startup environment, enjoys end‑to‑end ownership of ML systems, and has a strong quantitative background with proven production ML experience.
About Ramp
Ramp is building the smart infrastructure for finance teams, embedded in the transaction flow of every dollar a business spends. We automate how over $275B in annualized spend flows in and out of 85,000+ companies: authorizing payments, flagging risk, categorizing spend, and closing books.
The problems are high-stakes, data-dense, and unforgiving.
We hire people with high agency and high urgency. We look for slope over intercept. We care less about where you trained and more about what you’ve built. At Ramp, everyone is a builder who owns problems end to end and makes consequential decisions that shape the outcome.
The median Ramp customer saves 7.5% and grows revenue 16% in their first year – far in excess of businesses operating without Ramp. We believe every ambitious company deserves the same.
If you want to build systems that directly shape how companies move and manage billions, Ramp is the place to do it.
About the Role
We’re seeking someone to lead the future of fraud machine learning at Ramp. In this role, you will help build core machine learning models, design data architectures, and set strategic roadmaps to help Ramp mitigate fraud-related threats while minimizing the friction experience by legitimate users. You will partner closely with product and engineering counterparts across model design, implementation, execution, and analysis.
What You’ll Do
What You Need
Nice-to-Haves
Benefits available to all full-time Ramp employees (Global)
United States
Canada
United Kingdom
Referral Instructions
If you are being referred for the role, please contact that person to apply on your behalf.
Other notices
Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.
Beware of recruiting scams: Ramp will only contact you through official @Ramp.com email addresses and will never ask for payment or sensitive personal information during the hiring process.
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