Stripe

The Radar ML team builds the machine learning systems that power Stripe’s Radar fraud and abuse product suite. Our models make real-time decisions across a significant share of internet commerce, helping businesses stop fraud, increase authorization, and grow safely. By turning economy-scale datasets into compelling ML products, the team directly improves customer outcomes and drives meaningful revenue for Stripe. The team is growing and expanding into multiple new areas, building abuse protections across the full customer life-cycle, adaptive and customizable fraud systems for enterprises, and risk intelligence for over 50 global payment methods. You will own ML problems from conception to production, analyzing new fraud and abuse patterns, experimenting with model architectures, designing evaluations, deploying models, and monitoring performance. Your work may include developing transformer architectures for payment data, building graph-powered intelligence, leveraging LLMs to detect emerging attacks, or rapidly prototyping new protections.

Stripe is seeking product-minded engineers to join the Builder Experience Team, which focuses on improving how Stripe's product teams build, ship, and iterate on products. This team is AI-native and reimagines workflows using AI agents and automation to address fragmented and manual processes. The role involves identifying high-friction areas in the product development lifecycle, prototyping new approaches, and scaling successful experiments into solutions used across Stripe. You will work across the full stack, combining traditional software engineering with emerging AI capabilities to discover the right product, interface, and technical architecture in ambiguous problem spaces.

Stripe is seeking an AI Engineer to join the Solutions Architecture team. This role involves embedding directly with Solutions Architects to understand their workflows and build production-quality tools, agents, and automation that enhance their productivity. You will focus on high-leverage opportunities, transforming how the team operates by scaling individual solutions to organizational capabilities. The goal is to measurably improve SA productivity through accelerated engagements and transformed workflows, working at the intersection of engineering and business impact.

Stripe is seeking a Backend Engineer for its Core Technology team. This role involves working on critical tier0 infrastructure systems, including compute, networking, document databases, distributed caching, and high-assurance engineering. The team builds the foundational platform that enables Stripe products and services to operate at scale, driving reliability, availability, efficiency, and scalability. You will design, build, test, and ship high-quality code daily, contributing to a great customer experience for both internal and external Stripe teams.

Growth Platform at Stripe builds machine learning systems to help businesses discover and utilize Stripe products. These recommendations are integrated across various platforms including the Dashboard, email, onboarding, documentation, and AI agent interfaces. The team combines business understanding with models to determine the most useful recommendations, optimal timing, and effective learning from outcomes. Their work encompasses recommendation and ranking models, contextual bandits, agent-based recommendations, and the underlying data and evaluation systems, aiming to drive business growth through relevant product adoption while maintaining a positive user experience.

Stripe is seeking a Machine Learning Engineer for its Link Fraud and Auth team. This role involves building and operating models and risk decisioning systems to protect Link while enabling legitimate payments. You will manage the full machine learning lifecycle, from analyzing fraud patterns and identifying opportunities to developing, deploying, monitoring, and improving models in production. Your work will directly impact Link's fraud performance, authorization rates, and expansion into new products and payment experiences, contributing to Stripe's mission to increase the GDP of the internet.

Financial Connections is Stripe's open banking platform, enabling businesses to securely access consumer-permissioned financial data. Our platform connects to thousands of financial institutions, powering use cases from account verification to risk assessment to personal financial management. Across the Financial Connections Engineering org, we focus on delivering high-quality, enriched bank data at scale — building the ML systems that transform raw financial data into actionable signals for both internal Stripe teams and external merchants. Our ML work spans transaction categorization, risk scoring, data enrichment, and the development of intelligent systems that improve data quality across our network. We operate at the intersection of fintech infrastructure and applied machine learning, solving problems that directly impact Stripe's ability to serve millions of businesses and consumers.

The Radar ML team builds the fraud detection models that protect Stripe's $1.9 trillion payment network from fraud. The team owns over 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. The team's models also power the Radar product suite that tens of thousands of businesses use to screen payments and manage fraud. 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.

Stripe is a financial infrastructure platform for businesses, aiming to increase the GDP of the internet. The Dashboard Product team is dedicated to creating world-class user experiences for Stripe merchants through meticulous attention to detail and craft. This team focuses on perfecting Stripe's main merchant interface, the Dashboard, by ensuring intuitive, reliable software and distilling front-line insights into shared components. They are also exploring how AI agents can unlock new creative possibilities for merchant interactions.

The Link team is building the premier consumer network for next-generation commerce, leveraging over 300 million registered consumers to pioneer the future of Identity, Consumer Finance, and AI-driven transactions. The Consumer Preference team specifically focuses on enhancing the Link experience across web applications and agents, creating a wallet product that empowers consumers with financial insights, rewards, and secure transaction capabilities. As a Staff Full Stack Engineer, you will lead the design and delivery of new consumer features, taking ambiguous product opportunities from initial concept through validation and final launch. This hands-on role involves owning large, cross-functional projects, leading engineering teams, and making critical architectural decisions to balance quality with rapid iteration.

Stripe is seeking a Staff Software Engineer to join the Machine Learning Platform team. This role involves technical leadership and significant contributions to the evolution of platforms powering Stripe's ML-driven products. You will influence investments and strategy, enhance system reliability, security, and usability, and collaborate cross-functionally to amplify ML's impact across the company. The team builds and maintains the platforms and services that enable ML engineers and data scientists to develop and deploy models from prototype to production at scale, covering areas like ML training, model serving, feature computation, observability, and agentic AI capabilities.