From a data perspective, Stripe handles over $1.4T in payments volume per year, which is roughly 1.3% of the world’s GDP . We process petabytes of financial data using our ML platform to build features, train models, and deploy them to production. We focus on seeing how LLMs can solve some of our hardest problems in merchant risk and understanding how we can align language to our immense ocean of payments data. Some of our latest innovations have been around understanding how to best represent payments using transformers and enabling entirely new product ideas that are only made possible by GenAI.

As a Machine Learning Engineer on the Foundation Model team, you'll solve some of Stripe's most challenging technical problems that span multiple teams and directly impact our research and engineering efforts around building the Foundation Models that power our payments and risk solutions . You'll be responsible for both hands-on technical contributions and driving strategic initiatives that shape how ML systems operate at scale across Stripe.

• 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
• 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.
• 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.
• 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.
• Experience with a large-scale, data-rich product in a domain such as payments, commerce, search, or social media.
• Knowledge of the challenges and opportunities in applying ML to fraud prevention, merchant intelligence, or financial services.

Published research or open source contributions in AI/ML or related fields