Machine Learning Engineer, Radar

Stripe·Seattlemid

In short

→Construyes modelos de deep learning en tiempo real para detectar fraude en pagos globales.
→Trabajas desde la investigación hasta el despliegue, impactando directamente en el sistema financiero de Stripe.
→Eres parte clave en crear productos nuevos para combatir fraudes como el robo de tokens y abusos de pruebas gratuitas.

Proficiency in English required for technical collaboration

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The questions they'll ask you

1. ¿Cómo diseñarías un experimento para evaluar el impacto de un nuevo modelo de detección de fraude en producción?

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💵 USD · Remote · No visa

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What they ask for

✓2+ años de experiencia en modelos de ML en producción
✓Dominio de Python, SQL, Spark y PyTorch
✓Conocimientos sólidos en análisis de datos, estadística y diseño de experimentos
✓Interés activo en avances recientes en ML
✓Habilidades de ingeniería de software para construir soluciones robustas
✓Capacidad para colaborar con clientes clave en el desarrollo de productos

Don't tick every box? That's normal — your free dossier shows your gaps and how to cover them in the interview.

PythonSQLSparkPyTorchdeep learningreal-time systemsML deploymentexperiment designfraud detectionproduction ML

Who should you write to at Stripe?

Your free dossier identifies the people who'd interview you — their background, what they value, and how to reach out so you stand out before applying.

Who we are About Stripe 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. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone’s reach while doing the most important work of your career. About the team 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. The team's models also power the Radar product suite that tens of thousands of businesses use to screen payments and manage fraud. Radar is growing fast, and the team is actively building new products to protect against AI token theft, free trial abuse, and scripted attacks. What you’ll do 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 Who you are We’re looking for someone who meets the minimum requirements to be considered for the role. If you meet these requirements, you are encouraged to apply. The preferred qualifications are a bonus, not a requirement. Minimum 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 solut

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