Machine Learning Engineer

About The Company
Patreon is a leading media and community platform dedicated to empowering creators worldwide. With over 300,000 creators leveraging the platform, Patreon enables them to connect with their biggest fans through exclusive content and experiences. The platform offers diverse engagement options including paid memberships, free memberships, community chats, live events, and direct sales via one-time purchases. Since its inception, Patreon has generated more than $8 billion in revenue, facilitated over 60 million free memberships, and supports over 10 million paying fans each month. Our mission is straightforward: to fund the creative class and foster a thriving ecosystem where creators can succeed. As a pioneer in this space, we are committed to innovating and expanding our platform to better serve our community of creators and fans alike.
About The Role
We are seeking a highly skilled Staff Machine Learning Engineer to join our Relevance team, based in San Francisco or New York, with a hybrid work model requiring in-office presence two days per week. In this role, you will be instrumental in developing and deploying content and creator classification systems that enhance discovery, recommendations, and platform insights. Your expertise will help power features that improve content relevance, search accuracy, and creator-fan matching, ultimately enriching user experience and platform engagement. You will lead the design, analysis, and implementation of machine learning pipelines, working closely with cross-functional teams including product, engineering, design, legal, and trust & safety. Your work will directly influence how creators and fans connect, discover new content, and engage with the platform on a deeper level.
Qualifications

• 8+ years of experience in machine learning engineering or applied ML roles
• Proficiency in natural language processing, topic modeling, and clustering techniques
• Experience with end-to-end machine learning workflows: data analysis, model building, deployment, and monitoring
• Hands-on experience working with unstructured content such as audio, video, text, and images
• Strong coding skills in Python and familiarity with common ML/NLP libraries
• Experience with distributed systems, production pipelines, and model deployment frameworks
• Excellent collaboration skills across engineering, data science, and product teams
• Effective communication skills with the ability to document and present technical work clearly
• Bachelor’s or Master’s degree in Computer Science, Machine Learning, Statistics, or related field

Responsibilities

• Design, build, and deploy machine learning pipelines that generate taxonomies of creators, content, and risk profiles
• Conduct exploratory data analysis and develop proof-of-concept models to identify opportunities for platform enhancement
• Collaborate with cross-functional teams to design and implement effective ML solutions aligned with product goals
• Analyze and prepare training datasets, utilizing crowdsourcing and data labeling techniques as needed
• Train, tune, and iterate on machine learning models using innovative techniques and best practices
• Deploy models into production environments, ensuring scalability and robustness
• Monitor model performance, troubleshoot issues, and refine models to address performance gaps
• Translate complex data insights into actionable recommendations for stakeholders
• Communicate technical concepts effectively to non-technical partners and leadership
• Act as a cultural and technical leader within the Relevance team, fostering innovation and best practices

Benefits

• Competitive salary and equity plans
• Comprehensive healthcare coverage
• Flexible time off and paid holidays
• Recharge days and wellness programs
• Commuter benefits and lifestyle stipends
• Learning and development stipends to support continuous growth
• Parental leave policies
• 401(k) plan with matching contributions

Equal Opportunity
Patreon is proud to be an equal opportunity employer. We are committed to creating an inclusive environment where all employees and applicants are treated with respect and fairness, regardless of age, race, color, ancestry, national origin, religion, disability, sex, gender identity or expression, sexual orientation, veteran status, or any other protected class. We encourage candidates from diverse backgrounds to apply.