stripe
Machine Learning Engineer, Radar
At a Glance
- Location
- Seattle
- Experience
- 3+ years
- Posted
- 2026-06-23T17:00:25-04:00
Key Requirements
Required Skills
Domain Knowledge
- Engineering
Requirements
Over 3+ years industry experience building machine learning applications in large scale distributed systems.
2+ year of experience working within a team responsible for developing, managing, and optimizing ML models or ML infrastructure
Experience designing and training machine learning models to solve critical business problems
Experience performing analysis, including querying data, defining metrics, or slicing and dicing data to model performance and business metrics
Proven track record of building and deploying machine learning systems that have effectively solved critical business problems
Experience in adversarial domains like Payments, Fraud, Trust, or Safety
Responsibilities
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
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.
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
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
About the Company
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.