Description
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.
The Radar ML team builds the fraud detection models that protect Stripe's $1.9 trillion payment network from fraud. The team owns 10 real-time deep learning models that must constantly evolve to stay ahead of fraudsters. Each ML improvement translates directly into dollar impact for Stripe and its users.
In this role, you will own ML work across the full lifecycle: researching new fraud patterns, building and deploying models, and sharing results directly with top Stripe customers. You will have opportunities to optimize Stripe’s most intensive ML models, and opportunities to ship 0-to-1 products from scratch.
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
Requirements
- 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
Preferred Qualifications
- Strong software engineering skills and ability to design ML solutions through entire product stack
- Experience building and optimizing real-time, low-latency ML infrastructure at scale
- Experience applying ML to fraud detection, integrity, trust and safety, or a closely related domain