11 hours ago
Responsibilities
- Build, train, evaluate, and deploy ML models to detect fraud across Stripe’s global payments network.
- Research emerging fraud patterns such as token theft and develop ML solutions to address them.
- Apply deep learning advances to improve model quality and detection rates at scale.
- Co-build new fraud and abuse products directly with top Stripe users.
Requirements
- At least 2 years of experience training, evaluating, and deploying ML models in a production environment.
- Proficiency in Python, SQL, Spark, and PyTorch.
- Strong knowledge of production ML systems, data analysis, statistics, and experiment design fundamentals.
- Active interest in current ML developments and applying them to business problems.
- Preferred: strong software engineering skills and the ability to design ML solutions across the full product stack.
- Preferred: experience building and optimizing real-time, low-latency ML infrastructure at scale.
- Preferred: experience applying ML to fraud detection, integrity, trust and safety, or a closely related domain.
Tech Stack
Categories
About Stripe
Stripe builds financial infrastructure for internet businesses, offering APIs and tools for online and in‑person payments, subscriptions, marketplaces/payouts, fraud prevention, identity, tax, issuing, and treasury. It monetizes through per‑transaction fees and SaaS pricing for advanced products. Founded in 2010 and headquartered in South San Francisco, Stripe is privately held and serves companies from startups to large enterprises worldwide.