ML Engineer, Payments

About The Company Stripe is a leading financial infrastructure platform dedicated to empowering businesses worldwide. Serving millions of companies ranging from global enterprises to innovative startups, Stripe provides seamless solutions for accepting payments, expanding revenue streams, and accelerating new business opportunities. Our mission is to increase the GDP of the internet, fostering economic growth by building robust, scalable, and secure payment infrastructure. With a focus on innovation and technology, Stripe aims to make financial services accessible to everyone, everywhere, enabling entrepreneurs and organizations to thrive in the digital economy.

About The Role We are seeking a highly skilled Machine Learning Engineer to join our Payments ML Accelerator team. In this role, you will develop and deploy advanced machine learning models that directly influence Stripe’s payment products and core business metrics. Your work will involve the entire ML lifecycle, from research and experimentation to production deployment, focusing on high-impact problems such as fraud detection, authorization optimization, and other complex payment challenges.

As part of a central ML innovation hub, you will collaborate closely with product and engineering teams to identify scalable solutions and build foundational models that serve as a basis for future capabilities. This position offers a unique opportunity to work on cutting-edge ML techniques, contribute to strategic initiatives, and shape the future of payments technology at Stripe.

Qualifications

• Minimum of 7 years of industry experience in end-to-end machine learning development and deployment
• Proficiency in Python, Scala, and Spark
• Deep expertise in deep learning and large language models (LLMs)/foundation models
• MS or PhD degree in a quantitative field such as computer science, mathematics, physics, or statistics
• Experience developing streaming feature pipelines and integrating ML models into production environments
• Strong understanding of data manipulation, querying, and analysis techniques
• Knowledge of evaluating and deploying ML solutions at scale
• Excellent technical judgment, problem-solving skills, and ability to translate ideas into scalable systems
• Ability to work effectively in ambiguous situations, take initiative, and drive projects forward

Responsibilities

• Design and implement deep learning architectures and foundation models to address key payment challenges involving merchants, issuers, and customers
• Identify high-impact opportunities and develop strategic ML roadmaps to support long-term innovation goals
• Architect generalizable ML workflows that enable rapid scaling and optimize online performance
• Deploy machine learning models in production environments, ensuring operational stability and performance
• Experiment with industry-leading ML techniques and evaluate their applicability to Stripe’s products
• Collaborate with ML infrastructure teams to shape platform capabilities and improve deployment pipelines
• Work closely with product teams to translate business needs into effective ML solutions
• Explore emerging ML research and incorporate novel techniques to enhance product offerings

Benefits

• Competitive annual salary range of $212,000 – $318,000 (US-based roles)
• Equity options and potential bonuses or sales commissions
• Comprehensive health, dental, and vision insurance plans
• 401(k) retirement plan with company matching
• Wellness stipends and other employee benefits
• Flexible work arrangements, including remote work options
• Opportunities for professional growth and development within a global fintech leader

Equal Opportunity

Stripe is an equal opportunity employer committed to fostering an inclusive environment for all employees. We celebrate diversity and are dedicated to creating a workplace where everyone feels valued and empowered. We do not discriminate based on race, color, religion, gender, sexual orientation, gender identity, national origin, age, disability, or any other protected characteristic.