Stripe
Machine Learning Engineer, Radar
Seattle, South San Francisco +1 · Full-time · Posted Jun 23, 2026
- Location
- Seattle, South San Francisco
Seattle, Washington, United States - Experience
- 5+ years developing, evaluating, and deploying machine learning models in a production environment.
About the job
Owns end-to-end production machine learning systems that detect fraud and abuse across Stripe’s global payments network.
What you'll do
- Lead ML projects from problem definition through deployment, monitoring, and iteration.
- Build and operate models and production systems for detecting fraud and abuse.
- Investigate emerging threats and partner across disciplines to deliver Radar products.
What they ask for
- 5+ years developing, evaluating, and deploying machine learning models in production.
- Track record leading ML projects from problem definition to production with measurable impact.
- Deep foundations in machine learning, statistics, model evaluation, and experiment design; strong production software-engineering skills.
- Experience designing and operating production ML systems and mentoring engineers or technically leading projects.
Nice to have
- Experience applying ML in fraud or another adversarial domain; developing or productionizing deep learning, graph-learning, or LLM-based approaches.
- Experience building low-latency ML systems at scale, owning operational health, rapidly building 0→1 products, or creating AI-assisted tooling.
Tools
transformer models, graph intelligence, LLMs
AI focus
Builds machine learning systems for fraud and abuse detection, including transformer models over payment data, graph intelligence across consumers, and LLMs that detect emerging attacks; may also build AI-assisted workflows and tools.
Model-written summary · the original posting is authoritative