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Stripe is looking to solve some of the most challenging problems in payments and fraud by leveraging machine learning and generative AI technologies to optimize access and risk, and to transform how Stripe uses ML to power its entire product suite.

Requirements

• 5+ years of experience building and shipping ML models that power AI/ML product features, with a strong emphasis on modern technologies such as DNNs, Transformers, and Foundation Models.
• Strong programming skills in Python with demonstrated ability to write production-quality code
• A strong experimental mindset, with a proven track record of identifying, prototyping, and validating SOTA machine learning methods to enhance model performance.
• Proven ability to shepherd large, complex ML projects and drive transformational change in an organization.
• Deep passion for solving really interesting problems and for building the latest technologies rather than relying on outdated methods.
• Experience with a large-scale, data-rich product in a domain such as payments, commerce, search, or social media.

Responsibilities

• Develop foundation models for payments, merchants, and consumers that span Stripe product areas.
• Fine-tune and optimize LLMs using SOTA techniques, including multimodal alignment, knowledge distillation, quantization, and reasoning to build highly specialized models.
• Drive technical excellence through hands-on contributions to the design and development of state-of-the-art AI/ML systems, conducting architecture reviews, and maintaining high code quality
• Partner with engineering and product leaders across Stripe to identify and prioritize foundational investments such as foundation models, assistants, and agents that unlock new capabilities for product teams
• Contribute to Stripe's technical strategy by representing AI/ML engineering perspectives in company-wide technical decisions and roadmap planning
• Mentor ML engineers across Stripe on ML experimentation, helping teams navigate complex technical trade-offs, and adopt platform capabilities effectively

Other

• A PhD or Master's degree with a research-oriented background, with the ability to dive into research papers and stay current with academic publications.
• Published research or open source contributions in AI/ML or related fields
• Ability to work closely with partners in Risk, Payments, and Support to build transformative technologies
• Ability to drive strategic initiatives that shape how ML systems operate at scale across Stripe
• Ability to mentor ML engineers across Stripe