About the role
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 Transaction Risk team builds the machine learning systems behind Stripe Radar, helping businesses prevent fraud and abuse while letting legitimate customers through. We combine intelligence from across Stripe’s global network with real-time models and AI agents to protect businesses across the customer lifecycle, from signup and free trials to payments and ongoing usage, with a growing focus on the emerging threats facing AI companies.
The team is growing, and expanding into multiple new areas. We are building abuse protections across the full customer life-cycle and solving emerging token fraud problems to make Stripe the default fraud and abuse solution for AI.
What you’ll do
You will own major ML systems and initiatives from problem definition to production. You'll find where ML can make the biggest difference, design the approach, build and ship models and the systems around them, and keep improving them as data, users, and attackers change.
Your work may include protecting businesses from abuse across the customer lifecycle, building adaptive and customizable fraud systems for Stripe's largest users, or extending risk intelligence to 50+ global payment methods. Across all of these, you'll use modern approaches, such as transformer models over payment data, graph intelligence across consumers, and LLMs that detect emerging attacks.
You will have opportunities to ship 0→1 products, and to improve mission-critical ML models operating at Stripe scale, often driving several efforts in parallel and setting the technical bar for the team.
Responsibilities
- Lead the design and delivery of ML projects end to end, from framing the problem and sizing the opportunity through deployment, monitoring, and iteration.
- Build, train, evaluate, and deploy models that detect fraud and abuse across Stripe’s global network, and own the production systems they run on.
- Investigate emerging fraud and abuse patterns, decide where ML can have the most impact, and quickly turn those insights into shipped protections.