Machine Learning Intern (PhD) - Summer 2026

🇺🇸 San Francisco, California
$0 - $0 Annual
Posted 4 months ago
Expires June 9, 2026

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+ in revenue generated 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 Intern to support our mission.

This role is based in San Francisco or New York and open to those who are able to be in-office 3 days per week on a hybrid work model.

About the Role

As a Machine Learning Intern, you’ll join one of our ML teams and work closely with experienced machine learning engineers, product managers, designers, and engineers. You’ll gain hands-on experience across the end-to-end ML development lifecycle — from exploratory data analysis and model prototyping to production deployment and monitoring. With mentorship and cross-functional collaboration, you’ll own a well-defined ML project expected to ship to production by the end of the internship, making meaningful contributions to systems that support creators and fans worldwide.

In this role, you will:

- Ship a real-world ML feature that directly impacts the creator economy! You’ll work on a well-defined machine learning project in close partnership with a dedicated mentor, with the goal of shipping a complete, production-ready solution by the end of the internship. This includes training and iterating on ML models, writing high-quality, production-level code, and building backend components to...

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