About this role
This Machine Learning Engineer, Radar role is based in Seattle at Stripe and suits an individual with professional production experience in machine learning who wants to build fraud detection systems. The position involves developing and scaling deep learning models to protect a massive global payment network from malicious activity.
Role Overview
The Machine Learning Engineer, Radar position at Stripe involves creating and maintaining fraud detection models that safeguard a large payment network. The team operates multiple real-time deep learning models that evolve continuously to counter emerging threats. Practitioners in this function handle the complete lifecycle of machine learning projects, from initial research into new fraud patterns to model deployment and customer collaboration.
Key Responsibilities
Requirements
Nice to Have
Skills and Tools
About the Company
Stripe operates as a financial infrastructure platform utilized by businesses ranging from startups to large enterprises to accept payments, expand revenue streams, and manage business opportunities. The organization focuses on increasing the gross domestic product of the internet.
How to Apply
Interested candidates should apply on the official Stripe careers page.
Skills and tech stack
Questions candidates ask
Where is this job located?
The position is located in Seattle.
What is the primary focus of the Radar ML team?
The team builds fraud detection models to protect Stripe's payment network and develops products to prevent issues like AI token theft, free trial abuse, and scripted attacks.
How many years of experience are required?
Candidates need at least two years of experience training, evaluating, and deploying machine learning models in a production environment.
What programming languages and frameworks are required?
Proficiency in Python, SQL, Spark, and PyTorch is required.