Staff Machine Learning Engineer, Trust & Safety

Patreon is the best place for creators to fire up their fandoms, share exclusive work, and turn their passions into lasting creative businesses. Over 250,000 podcasters, writers, musicians, artists, and other creative people use Patreon to reach their biggest fans directly and earn an income for the value they provide. Creators can offer paid memberships that unlock access to exclusive work and community, or sell individual digital items from their own Patreon shops.

Ultimately, our goal is simple: fund the creative class. And we’re leaders in that space, having sent over $3.5 billion to creators since our founding. We’re continuing to invest heavily in building the best creator tools with the best team in the creator economy, and are looking for a Machine Learning Engineer to support our mission.

This role is a Remote friendly role or open to those who are able to be in-office 2 days per week on a hybrid work model in our San Francisco or New York office.

About the Role

• Work on cutting edge Trust & Safety Machine Learning solutions for detecting fraud, mitigating fake accounts and account takeovers, detecting image and text policy violations, reducing data scraping, and others.

• Conduct exploratory data analyses and proof-of-concept machine learning models to understand opportunities and potential project impact.

• Collaborate with cross-functional partners, such as product, engineering, design, legal, and trust and safety to design effective machine learning solutions.

• Analyze and prepare training data, including using crowdsourcing and Large Language Model data labeling techniques.

• Train and iterate on machine learning models using novel techniques, including state-of-the-art image models, and Large Language Models for text classification.

• Deploy machine learning models to production and write backend code when necessary to properly deploy the model.

• Debug models when observability shows performance gaps, and iterate on models.

About You

• You have experience creating end-to-end ML solutions for the Trust & Safety space: analyzing data, building and iterating on machine learning models, writing production-level code and shipping to production, monitoring performance, and A/B testing.

• You write clean and robust code in Python or other programming languages and have a keen eye for detail in code reviews.

• You have experience debugging complex systems with a systematic approach.

• You have a curious mindset and dive deeply into datasets to understand our product and customers.

• You have solid communication skills and write clear documentation.

• You have a growth mindset and aspire to continuously improve …