Machine Learning Engineer, Payment Intelligence

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 Engineering (PIME) 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

We are looking for Machine Learning Engineers to own the end-to-end lifecycle of applied ML model development and deployment in service of consumer facing products like Radar, Adaptive Acceptance, and Identity. You will work closely with software engineers, machine learning engineers (MLE), data scientists (DS), and ML platform infrastructure teams to design, build, deploy, and operate Stripe’s ML-powered payment decisioning systems, including improving existing ML models and developing new ML solutions.

Responsibilities

• Design and deploy new models using tools (such as Spark, Presto, XGBoost, Tensorflow, PyTorch) and iteratively improve verification and fraud models to protect millions of users from fraud
• Envision and develop new models for fraud detection i.e work with large payment datasets to find creative new methods of detecting and deterring fraudulent behavior.
• Propose new feature ideas and design real-time data pipelines to incorporate them into our models.
• Integrate new signals into ML pipelines, derive new ML features, and build workflows to make this process fast
• Integrate new models and behaviors into Stripe’s core payment flow
• Collabor