Machine Learning Engineer, Payments ML Accelerator

Role Overview

Join Stripe's Payments ML Accelerator team as a Machine Learning Engineer to develop foundational ML capabilities that drive innovation across payment products. You'll work on high-impact problems spanning the entire ML lifecycle, from research and experimentation to production deployment.

Key Responsibilities

• Design and deploy deep learning architectures and foundation models for payment challenges (fraud detection, authorization optimization, etc.)
• Identify high-impact opportunities and drive the long-term ML roadmap through well-scoped initiatives
• Architect generalizable, reusable ML workflows that enable rapid scaling and optimized online performance
• Deploy ML models to production and ensure operational stability
• Experiment with advanced ML solutions and evaluate their potential for business applications
• Explore cutting-edge ML techniques and assess their applicability to payment problems
• Collaborate with ML infrastructure teams to shape new platform capabilities
• Partner with product and engineering teams to translate ideas into measurable impact

Requirements

• Minimum 7 years of industry experience in end-to-end ML development on a machine learning team
• Proven track record of bringing ML models to production
• Proficiency in Python, Scala, and Spark
• Strong expertise in deep learning and LLM/foundation models
• Comfortable with ambiguity, self-directed, and action-oriented
• Technical judgment and ability to design scalable systems

Preferred Qualifications

• MS/PhD in a quantitative field (computer science, math, physics, statistics, ML/AI)
• Experience with data manipulation, analysis, querying, metrics definition, and hypothesis evaluation
• Familiarity with niche and emerging ML solutions
• Knowledge of streaming feature pipelines