Patreon is the best place for creators to build memberships by providing exclusive access to their work and a deeper connection with their communities. We’re building a content and community platform where creators can engage directly with their fans and monetize their creativity, while maintaining full ownership over the work they make and the communities they create.
We’re leaders in the membership space with 250,000+ active creators and over $3.5 billion paid directly to creators on our platform. Our team is building tools to optimize the creator-to-fan relationship, including native video, enhanced podcasting features, improved creation tools, and new community experiences. We’re continuing to invest heavily in building the most talented team in the Creator Economy and are looking for a Software Engineer – Machine Learning Backend to support our mission.
This role is based in San Francisco and open to those who are able to be in-office 2 days per week on a hybrid work model.
About the Role
- Lead our team in building a machine learning platform, including building a feature store, building observability on models, building interfaces with other systems, and developing model deployment processes and best practices.
- Work with Machine Learning Engineers in the team to design and implement robust, scalable machine learning systems in production.
- Be the expert in machine learning infrastructure and internal product code that interfaces with machine learning models.
- Develop internal tools for supporting our machine learning roadmap, including tools for active learning, visualization, and model explainability.
- Collaborate with cross-functional partners, such as product, engineering, design, legal, and trust and safety to design effective machine learning system solutions.
- Mentor team members on software design and code best practices.
- Debug machine learning systems when observability shows performance gaps.
- 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 working with databases (Redshift, Snowflake, BigQuery, ElasticSearch. Clickhouse etc.), building data pipelines (Airflow, Kafka/Kinesis, Hadoop/Hive, S3, etc.) and developing solutions for Machine Learning infrastructure (Databricks, AWS, Azure, etc.)
- You have experience debugging complex systems with a systematic approach.
- You have solid communication skills and write clear documentation.
- You have a growth mindset and aspire to continuously improve your soft and technical skills.
- You are energized about building the first version of systems and are passionate about empowering creators with new solutions.
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.
Patreon offers a competitive benefits package including and not limited to salary, equity plans, healthcare, unlimited paid time off, company holidays and recharge days, commuter benefits, lifestyle stipends, learning and development stipends, patronage, parental leave, and 401k plan with matching.
The posted range represents the expected salary range for this job requisition and does not include any other potential components of the compensation package, benefits and perks previously outlined. Ultimately, in determining pay, we'll consider your experience, leveling, location and other job-related factors.