Machine Learning Engineer, Payments ML Accelerator Job at Stripe in San Francisc

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.

The Team
The Payments ML Accelerator team is developing foundational ML capabilities that drive innovation across Stripe's payment products. We build deep learning models that tackle Stripe’s most complex payment challenges— from fraud detection to authorization optimization—and deliver measurable business impact. Our work combines advanced ML techniques with large‑scale data infrastructure to enable rapid experimentation and seamless deployment of AI‑powered solutions. As a central ML innovation hub, we work closely with product teams to identify high‑impact opportunities and implement scalable solutions that can be leveraged across the organization.

What You'll Do
As a machine learning engineer on our team, you’ll develop advanced ML solutions that directly impact Stripe’s payment products and core business metrics. Your role will span the entire ML lifecycle, from research and experimentation to production deployment. You’ll work on high‑leverage problems that require innovation in modeling, optimization, and system design. Where possible you’ll look beyond point solutions—designing approaches and architectures that are reusable, extensible, and serve as foundation models for future capabilities. The role demands strong technical judgment, deep knowledge of modern ML methods, and the ability to translate ideas into systems that deliver measurable impact. You’ll partner with product and engineering teams to identify opportunities where ML can move the needle today while setting Stripe up for long‑term success.

Responsibilities

Design and deploy deep learning architectures and foundation models to address problems across key payment entities such as merchants, issuers, or customers

Identify high‑impact opportunities, and drive the long‑term ML roadmap through well‑scoped high‑leverage initiatives

Architect generalizable ML workflows to enable rapid scaling and optimized online performance

Deploy ML models online and ensure operational stability

Experiment with advanced ML solutions in the industry and ideate on product applications

Explore cutting‑edge ML techniques and evaluate their potential to solve business problems

Work closely with ML infrastructure teams to shape new platform capabilities

Who You Are
We are looking for ML Engineers who are passionate about using ML to improve products and delight customers. You have experience developing streaming feature pipelines, building ML models, and deploying them to production, even if it involves making substantial changes to backend code. You are comfortable with ambiguity, love to take initiative, and have a bias towards action.

Minimum Requirements

Minimum 7 years of industry experience doing end‑to‑end ML development on a machine learning team and bringing ML models to production

Proficient in Python, Scala, and Spark

Proficient in deep learning and LLM/foundation models

Preferred Qualifications

MS/PhD degree in a quantitative field or ML/AI (e.g. computer science, math, physics, statistics)

Knowledge about how to manipulate data to perform analysis, including querying data, defining metrics, or slicing and dicing data to evaluate a hypothesis

Experience evaluating niche and upcoming ML solutions

Hybrid Work and Location
This role is available either in an office or a remote location (35+ miles or 56+ km from a Stripe office). Remote location is defined as being 35 miles (56 kilometres) or more from one of our offices. You would be welcome to come into the office for team/business meetings, on‑sites, meet‑ups, and events, but we expect you to regularly work from home rather than a Stripe office. Stripe does not cover the cost of relocating to a remote location. We encourage you to apply for roles that match the location where you currently live or plan to live.

Office‑Assisted Expectations
Office‑assigned Stripes should spend at least 50% of the time in a given month in their local office or with users. This balances collaboration and learning with flexibility.

Pay and Benefits
The annual US base salary range for this role is $212,000 - $318,000. For sales roles, the range provided is the On‑Target‑Earnings (OTE) range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. This salary range may be inclusive of several career levels at Stripe and will be narrowed during the interview process based on a number of factors, including the candidate’s experience, qualifications, and location. Applicants not located in the US may request the salary range for their location during the interview process.

Additional benefits for this role may include: equity, company bonus or sales commissions/bonuses; 401(k) plan; medical, dental, and vision benefits; and wellness stipends.

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In Summary: The Payments ML Accelerator team is developing foundational ML capabilities that drive innovation across Stripe's payment products . We build deep learning models that tackle Stripe’s most complex payment challenges . The role demands strong technical judgment, deep knowledge of modern ML methods, and the ability to translate ideas into systems that deliver measurable impact .

En Español:

Acerca de StripeStripe es una plataforma de infraestructura financiera para empresas. Millones de compañías, desde las empresas más grandes del mundo hasta las startups más ambiciosas, utilizan Stribe para aceptar pagos, aumentar sus ingresos y acelerar nuevas oportunidades comerciales. Nuestra misión es incrementar el PIB de Internet y tenemos un asombroso volumen de trabajo por delante. Esto significa que usted tiene una oportunidad sin precedentes para poner la economía global al alcance de todos mientras realiza los trabajos más importantes de su carrera. El equipo The Payments ML Accelerator está desarrollando capacidades fundamentales de aprendizaje informático que impulsan la innovación a través de los productos de pago de Stlipe. Construimos modelos de aprendizajes profundos que abordan los problemas más complejos de Strip desde la detección de fraude hasta la optimización de autorizaciones y el impacto medible en los servicios de pago. Trabajará en problemas de alto apalancamiento que requieren innovación en el modelado, optimización y diseño del sistema. Cuando sea posible buscará más allá de las soluciones puntuales diseñando enfoques e arquitecturas que sean reutilizables, extensibles y sirvan como modelos básicos para capacidades futuras. El papel exige un fuerte juicio técnico, un profundo conocimiento de los métodos modernos de ML y la capacidad de traducir ideas a sistemas que proporcionen un impacto medible. Se asociará con equipos de ingeniería y productos para identificar oportunidades donde ML puede mover la aguja hoy mismo mientras se establece Stripe para el éxito a largo plazo. Responsabilidades Diseñar e implementar arquiteturas profundas y modelos fundacionales para abordar problemas entre entidades claves de pago tales como comerciantes, emisores o clientes Identificar rápidamente oportunidades de alto impacto, y escalonar la hoja de ruta de funcionamiento a largo tiempo mediante iniciativas cerradas de alta apalanca generalizable para desarrollar proyectos de trabajo y mejorar las habilidades empresariales. Usted tiene experiencia en el desarrollo de canales de funciones de transmisión, la construcción de modelos ML y su implementación a la producción, incluso si esto implica realizar cambios sustanciales al código backend. Se siente cómodo con la ambigüedad, le encanta tomar iniciativa y tener un sesgo hacia la acción. Requisitos mínimos Un mínimo de 7 años de experiencia en la industria realizando desarrollos de extremo a extremo en un equipo de aprendizaje automático e introduciendo modelos ML Proficientes en Python, Scala y Spark Proficient in deep learning y modelos LLM/foundation Qualifications Preferred MS/PhD en un campo cuantitativo o ML/AI (por ejemplo ciencias informáticas, matemáticas, física, estadísticas) Conocimiento sobre cómo manipular datos para llevar a cabo análisis, incluidos los datos de consulta, definir métricas o recortar y dicing datos para evaluar una hipótesis Experiencia Evaluación del trabajo híbrido Este tipo de soluciones está disponible en una ubicación remota (35 kilómetros / 56 millas). Te animamos a solicitar puestos que coincidan con el lugar donde vives actualmente o planeas vivir. Office-Assisted Expectations Office-Assigned Stripes debe pasar al menos 50% del tiempo en un mes determinado en su oficina local o con los usuarios. Esto equilibra la colaboración y aprendizaje con flexibilidad. Pago y Beneficios El rango de salario básico anual estadounidense para este puesto es de $212,000 - $318,000.