Senior Machine Learning Engineer, Safety

Senior Machine Learning Engineer, Safety 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 Machine Learning Engineer to support our mission. This role is based in San Francisco or New York as an in-office 2 days per week on a hybrid work model or Remote. About the Team This role is part of the Safety Engineering team at Patreon. Safety Engineering is responsible for using engineering techniques to reduce risks to creators, fans, and Patreon. This includes content moderation, fraud detection, and account integrity. You’ll be joining a team with established machine learning engineers, with experience putting ML models into production to drive real impact. We partner closely with policy and Trust & Safety Operations to accomplish our mission. This team is part of Patreon’s risk org which includes Safety Engineering, Identity Engineering, and Information Security teams. About the Role - Explore data and real-world cases to develop signals and machine learning models that identify and reduce platform risk. - Partner with cross-functional teams (product, engineering, design, legal, Trust & Safety) to design practical ML solutions that fit real workflows. - Analyze and prepare training data, including working with crowdsourced labeling and human-in-the-loop processes. - Prototype, train, and iterate on machine learning models, using a mix of established and novel techniques. - Own the path from idea to production: deploy ML and signal-based models, and write backend code when needed to support them. - Build observability into models, debug performance gaps, and continuously improve based on real-world results. - Measure impact using offline evaluation and experiments such as A/B tests. About You - You’ve worked on end-to-end machine learning systems, from data exploration and signal development through model deployment, monitoring, and experimentation. - You write clean, reliable production code (Python or similar) and bring a thoughtful, detail-oriented approach to code reviews. - You’re comfortable debugging complex systems and use a systematic approach to understand what’s going wrong. - You’re naturally curious and enjoy digging into messy datasets to understand products, users, and edge cases. - You’re motivated by working on high-stakes, real-world problems where ML systems operate at scale and outcomes matter. - You communicate clearly, whether that’s writing design docs, explaining tradeoffs, or sharing results with partners. - You’re excited about building early versions of systems and seeing them grow into high-impact, widely used solutions. - You care deeply about using machine learning responsibly to support and protect creators, and you’re excited to grow your expertise in Trust & Safety over time. - Masters in Computer Science, Computer Engineering, a related field, or the equivalent OR a minimum of 5 years of Machine Learning experience. About Patreon Patreon powers creators to do what they love and get paid by the people who love what they do. Our team is passionate about making this mission and our core values come to life every day in our work. Through this work, our Patronauts: - Put Creators First | They’re the reason we’re here. When creators win, we win. - Build ... (truncated, view full listing at source)