Fraud ML Engineer — Real-Time, Remote

Stripe; Seattle (WA); Hybrid; USD 180,000 - 270,000; Full time

Benefits offered by this job

Equity

Bonus/Commission

401(k)

Medical, Dental, Vision

Wellness stipends

Job summary

Stripe is seeking a machine learning engineer to own fraud-detection work across the full lifecycle—from researching patterns to deploying models that protect Stripe’s global payments network.

You will optimize the Radar ML stack, ship 0‑to‑1 products, and collaborate directly with top Stripe customers to reduce fraud, abuse, and risk at scale. Hybrid/work options in the US are available.

Qualifications

• 2+ years of 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

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

Skills

Python

SQL

Spark

PyTorch

Data analysis

Statistics

Experiment design

Job description

Stripe is seeking a machine learning engineer to own fraud-detection work across the full lifecycle—from researching patterns to deploying models that protect Stripe’s global payments network.

You will optimize the Radar ML stack, ship 0‑to‑1 products, and collaborate directly with top Stripe customers to reduce fraud, abuse, and risk at scale. Hybrid/work options in the US are available.