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 ML organization optimizes each of the billions of dollars of transactions processed by Stripe annually on behalf of our customers, maximizing successful transactions while minimizing payment costs and fraud. We leverage ML to serve real-time predictions as part of Stripe’s payment infrastructure and risk controls. We own products like Radar, Adaptive Acceptance, and Identity end-to-end, operating lightning fast world-scale services and cutting-edge ML models. 

What you’ll do

You will work closely with software engineers, data scientists (DS), and platform infrastructure teams to design, build, deploy, and operate Stripe’s ML-backed payment decisioning systems. 

Responsibilities Design machine learning systems and pipelines for training and running machine learning models that improve the efficiency of transactions on Stripe. This could involve: Building prediction models for new aspects of transaction outcomes, like whether we expect to win a dispute given auto-submitted evidence. Improving the accuracy of our prediction models for transaction outcomes, like whether a payment will be accepted or declined by the card network, or disputed as fraudulent by a cardholder. Understanding our users’ business needs in order to evaluate model performance and improve the value model we use to evaluate transaction outcomes. Developing and evaluating new model architectures which improve the accuracy of our prediction models. Incorporate new features and sources of data. Writing simulation code on our distributed clusters to help us understand what would happen across different segments if we changed how we action our models. Integrating new models and behaviors into Stripe’s core payment flow. Collaborating with our machine learning infrastructure team to build support for new model types into our scoring infrastructure. Mentor engineers earlier in their technical careers to help them grow   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 2+ years industry experience working on machine learning applications 2+ years of industry experience deploying machine learning models in a production environment Experience designing and training machine learning models to solve critical business problems Knowledge about how to manipulate data to perform analysis, including querying data, defining metrics, or slicing and dicing data to evaluate a hypothesis Preferred qualifications An advanced degree in a quantitative field (e.g. stats, physics, computer science) and some experience in software engineering in a production environment. 3+ years years industry experience working on machine learning models in a production environment 3+ years of industry experience deploying machine learning models in a production environment Experience in payments and/or fraud