Machine Learning Engineer, Growth Platform

Stripe is hiring a Machine Learning Engineer for its Growth Platform team. The role builds and operates production machine learning systems for recommending products, content, and next steps to businesses, from problem definition through deployment and measurement. It partners across engineering, data science, product, marketing, and sales to improve user and business outcomes.

Responsibilities:

• Design, train, evaluate, deploy, and maintain models for recommendation, ranking, and personalized action selection across Growth Platform surfaces
• Improve contextual bandit and policy-learning approaches, including exploration, reward design, and how recommendations adapt to user context and feedback
• Build agent-based recommendation capabilities that use business context to identify relevant products and integration options, with evaluations that test recommendation quality and usefulness
• Develop reliable data and feature pipelines for training and inference. Improve data freshness, feature quality, and consistency between training and production
• Build reusable tooling for model evaluation, retraining, and safe rollout so the team can test and ship improvements faster
• Own the quality and operation of the team's ML components: write tested production code, monitor models and pipelines, investigate failures, and improve reliability, latency, and cost
• Design and analyze online experiments with data science partners. Connect offline evaluation to product adoption and incremental impact, with guardrails for dismissals, unsubscribes, and user experience
• Partner with product engineering to integrate models into recommendation delivery systems, and with ML infrastructure teams to use and improve Stripe's shared training, feature, and serving capabilities
• Work with product, marketing, and sales partners to identify problems that shared ML capabilities can solve, and make practical choices about where modeling adds value