Senior Machine Learning Engineer, Relevance

Patreon
San Francisco, US
Hybrid

Who this role is best for

Best suited to senior machine learning engineers with production deployment experience working in content discovery and recommendation systems.

Best fit for

  • Senior engineers who have shipped ML models to production in a collaborative team setting.
    — “Experience working in an end-to-end machine learning team environment
  • Candidates comfortable with cross-functional collaboration across product and engineering teams.
    — “Collaborate with cross-functional partners, such as product, engineering, design, legal, and trust and safety
  • Engineers who thrive on iterative model improvement and performance debugging.
    — “Debug models when observability shows performance gaps, and iterate on models

Things to consider

  • Hybrid work model requires two days per week in San Francisco or New York office.
    — “in-office 2 days per week on a hybrid work model
  • Role involves backend coding for model deployment beyond pure ML work.
    — “write backend code when necessary to properly deploy the model

How to stand out

  • Demonstrate specific examples of model debugging and iteration in past roles.
    — “Debug models when observability shows performance gaps
  • Highlight cross-functional projects where you translated product needs into ML solutions.
    — “partnering cross-functionally with Product, Data Engineering, and Trust & Safety
  • Showcase documentation skills with samples of technical writing for varied audiences.
    — “Writes clear technical documentation for both technical and non-technical audiences
Pace · Fast PacedCollaboration · HighAutonomy · MediumDecision Impact · TeamLevel · Senior

Derived from job-description analysis by Serendipath's career intelligence engine.

What success looks like

  • built and deployed machine learning models
  • improved platform relevance
Typical background
machine learningdata science

Skills & requirements

Required

Machine LearningData AnalysisModel TrainingProduction DeploymentDebugging

Preferred

Cross-functional Collaboration

Stack & domain

PythonMachine LearningData AnalysisModel TrainingBackend CodeCollaborationDebuggingCode ReviewsTechnical DocumentationFeedbackSearchRankingFeed RelevanceCreator-fan Matching

About the role

Original posting from Patreon via Ashby

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 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.

ABOUT THE TEAM

You'll join the Relevance team, whose mission is to build the ML systems that power how fans discover creators and how content surfaces across Patreon. The team is responsible for search, ranking, feed relevance, and creator-fan matching. You'll work closely with a small, collaborative group of MLEs on shared infrastructure, code reviews, and roadmap alignment, while partnering cross-functionally with Product, Data Engineering, and Trust & Safety to deliver measurable impact across the platform.

ABOUT THE ROLE

  • 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 data labeling techniques.
  • Train and iterate on machine learning models using novel techniques.
  • 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.

WHAT YOU'LL NEED

  • Experience working in an end-to-end machine learning team environment (typically 5+ years): analyzing data, building and iterating on machine learning models, writing production-level code and shipping to production, monitoring performance, and A/B testing.
  • Writes clean and robust code in Python or other programming languages, and provides substantive, constructive feedback in code reviews.
  • Experience debugging complex systems with a systematic approach.
  • Analyzes datasets thoroughly to develop product and customer insights.
  • Writes clear technical documentation for both technical and non-technical audiences.
  • Seeks and incorporates feedback on code, models, and technical approaches.
  • Bachelor's degree in Computer Science, Computer Engineering, or a related field, or the equivalent

We hire talented and passionate people from different backgrounds because workplace diversity and inclusion is critical to our ability to serve creators worldwide. If you’re excited about a role but your past experience doesn’t match with every bullet point outlined above, we strongly encourage you to apply anyway. If you’re a creator at heart, are energized by our mission, and share our company values, we’d love to hear from you.

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 with Craft | We sign our name to every deliverable, just like the creators we serve.
  • Make it Happen | We don’t quit. We learn and deliver.
  • Win Together | We grow as individuals. We win as a team.

Patreon is proud to be an equal opportunity employer. We provide employment opportunities without regard to age, race, color, ancestry, national origin, religion, disability, sex, gender identity or expression, sexual orientation, veteran status, or any other protected class. If you need a reasonable accommodation during the interview process, please let us know via email at accommodations@patreon.

Patreon offers a competitive benefits package including and not limited to salary, equity plans, healthcare, flexible time off, company holidays and recharge days, commuter benefits, lifestyle stipends, learning and development stipends, patronage, parental leave, and 401k plan with matching.

Patreon operates under a hybrid work model, where employees based in office locations are expected to come into the office two days per week, excluding sick time and paid leave. The goal of this policy is to be intentional about the in-person time we spend together to strengthen the feeling of community at Patreon. Candidates hired into remote-eligible roles are not expected to meet the same requirements.

At Patreon, we believe in fair and transparent pay. In compliance with New York and California pay transparency laws, we are sharing the expected salary range for this role.

The posted salary range is dependent on the location and the level. This range may encompass multiple levels within the role’s job family. The final offer will be based on candidate’s experience, skills, competencies, and geographic location, aligning with the appropriate job level within Patreon’s leveling framework. For remote employees located outside CA and NY, salary may vary based on location and local market conditions.

Patreon reserves the right to modify or update compensation and benefits at any time

Source: Patreon careers (Ashby)

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