# Machine Learning Engineer, Payment Intelligence

**Company:** [Stripe](https://hotfix.jobs/companies/stripe)
**Location:** Seattle, WA
**Role:** ML Engineering
**Experience:** 6+ years
**Skills:** Python, SQL, Spark, PyTorch, Deep Learning, Machine Learning, Fraud Detection, ML Infrastructure, Statistics, experiment design
**Posted:** 2026-07-16

> Build, train, evaluate and deploy ML models to detect fraud across Stripe's global payments network. Research emerging fraud patterns, apply deep learning advances, and co-build new fraud products with top customers. Requires 6+ years production ML experience.

## Job Description

## Responsibilities
- Build, train, evaluate, and deploy ML models that detect fraud across Stripe’s global payments network
- Research emerging fraud patterns like token theft and develop ML solutions to address them
- Apply advances in deep learning to improve model quality and detection rates at scale
- Co-build new fraud and abuse products directly with top users

## Minimum Requirements
- 6+ years of industry experience training, evaluating, and deploying ML models in a production environment
- Proficiency in Python and common data and ML frameworks like SQL, Spark, and PyTorch
- Strong knowledge of production ML systems; and data analysis, statistics, and experiment design fundamentals
- Active interest in the latest ML developments, and how they can be leveraged to solve business problems

## Preferred Qualifications
- Experience building and optimizing real-time, low-latency ML infrastructure at scale
- Strong software engineering skills and ability to design ML solutions through entire product stack
- Experience applying ML to fraud detection, risk modeling, or a closely related domain
- Experience designing ML products used by millions of users

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