Machine Learning Engineer, Payments ML Accelerator

Role overview

Machine Learning Engineer on Stripe’s Payments ML Accelerator team, building foundational ML capabilities that drive innovation across Stripe’s payment products. You’ll work on high-impact ML problems such as fraud detection and authorization optimization, taking models end-to-end from research through production deployment.

Responsibilities

• Design and deploy deep learning architectures and foundation models for payment entities (e.g., merchants, issuers, customers)
• Identify high-impact opportunities and drive the long-term ML roadmap through well-scoped, high-leverage initiatives
• Architect generalizable ML workflows that enable rapid scaling and optimized online performance
• Deploy ML models online and ensure operational stability
• Experiment with advanced / cutting-edge ML techniques, evaluating potential product applications
• Work closely with ML infrastructure teams to shape new platform capabilities
• Develop streaming feature pipelines and support production deployment, potentially involving substantial backend code changes

Requirements

• 7+ years of industry experience in end-to-end ML development and taking models to production
• Proficient in Python, Scala, and Spark
• Strong knowledge of deep learning and LLMs / foundation models

Preferred qualifications

• MS/PhD in a quantitative field (e.g., CS, math, physics, statistics) or ML/AI
• Experience with data manipulation for analysis, including querying data, defining metrics, and slicing/dicing to evaluate hypotheses

Work model / location

• Hybrid work: in-office or remote, with remote eligibility for those 35+ miles (56+ km) from a Stripe office
• In-office expectation: office-assigned Stripe employees spend at least 50% of time monthly in the local office or with users