Senior Staff Machine Learning Engineer

Senior Staff Machine Learning Engineer Patreon is a media and community platform where over 300,000 creators give their biggest fans access to exclusive work and experiences. We offer creators a variety of ways to engage with their fans and build a lasting business including: paid memberships, free memberships, community chats, live video, and selling to fans directly with one-time purchases. Ultimately our goal is simple: fund the creative class. And we're leaders in that space, with: - $10 billion+ generated by creators since Patreon's inception - 100 million+ free memberships for fans who may not be ready to pay just yet, and - 25 million+ paid memberships on Patreon today. We're continuing to invest heavily in building the best creator platform with the best team in the creator economy and are looking for a Senior Staff Machine Learning Engineer, Relevance to support our mission. This role is based in New York or San Francisco and open to those who are able to be in-office 2 days per week on a hybrid work model. About the Team The Relevance team builds the intelligence layer that powers discovery, personalization, and creator-fan connection across Patreon. We’re responsible for ML-driven systems behind search, recommendations, notifications, and content relevance — helping millions of fans find the right creators, and helping creators grow sustainable audiences. Our engineers work end-to-end across the ML stack: from data analysis and feature engineering to model training, deployment, and observability. We partner closely with product, infrastructure, and design to ensure our models don’t just perform well in theory — they deliver meaningful experiences in the product. This team is growing quickly and investing in foundational relevance systems that will power the next decade of Patreon’s creator economy. About the Role As a Senior Staff Machine Learning Engineer in Relevance, you’ll define and lead the technical direction for Patreon’s recommendation and search systems. You’ll architect large-scale ML systems that determine what fans see, how they discover creators, and how creators grow their audiences. You’ll own projects from prototype to production, including the data, modeling, and backend components. You’ll also build tools and simple frontend prototypes to visualize model results and demonstrate how relevance models surface in the product. This ability to show how ML decisions appear in the user experience is key to how we connect technical work to creator impact. You’ll mentor other ML engineers, influence multi-team technical strategy, and collaborate with cross-functional leaders across Product, Data Science, and Infrastructure. Your work will define the standards and systems that future ML teams at Patreon build upon. In this role, you will: - Design and build large-scale ranking, search, and recommendation systems that power discovery across the platform. - Architect and productionize end-to-end ML pipelines (data ingestion, feature generation, model training, evaluation, deployment, and monitoring). - Prototype visualizations for the impact of new ML models to help bridge collaboration with product and design partners. - Develop embedding systems and retrieval models that serve millions of users in real time. - Establish and evolve ML observability and performance monitoring for relevance metrics. - Partner with cross-functional leaders to align on roadmap, goals, and impact. - Mentor and guide engineers, fostering a high bar for technical excellence and experimentation. About You You’re a senior technical leader who thrives in building systems from 0→1. You’re deeply familiar with the challenges of scaling search and recommendation models, and you enjoy operating at the intersection of modeling, systems, and product. You have experience bringing ML models to production at scale — and you care just as much about how they impact users as how they perform in offline metrics. You commun ... (truncated, view full listing at source)