Staff Machine Learning Engineer, Content Success

Job description

About Pinterest

Millions of people across the world come to Pinterest to find new ideas every day. It’s where they get inspiration, dream about new possibilities and plan for what matters most. Our mission is to help those people find their inspiration and create a life they love. In your role, you’ll be challenged to take on work that upholds this mission and pushes Pinterest forward. You’ll grow as a person and leader in your field, all the while helping Pinners make their lives better in the positive corner of the internet.

Creating a life you love also means finding a career that celebrates the unique perspectives and experiences that you bring. As you read through the expectations of the position, consider how your skills and experiences may complement the responsibilities of the role. We encourage you to think through your relevant and transferable skills from prior experiences.

Our new progressive work model is called PinFlex, a term that’s uniquely Pinterest to describe our flexible approach to living and working. Visit our PinFlex landing page to learn more.

Pinterest helps Pinners discover and do what they love. The Content Success team is responsible for ensuring that Pinners see fresh new products, ideas, and inspiration in their recommendations and that Content Producers receive value from the platform through exposure, engagement, and monetization. We are looking for a Staff Machine Learning Engineer who can drive the team’s technical direction, be hands-on in developing new integrations with recommendation systems, and make an impact on Pinterests top-line metrics.

What You'll Do

  • Identify opportunities for improving fresh content distribution, define what success looks like and develop solutions in partnership with cross-team surface owners.
  • Own the technical vision and direction of the Content Success team.
  • Act as the glue between content acquisition and recommendation pods becoming the expert in both these areas.
  • Solve difficult technical challenges such as:
    • How to build new ML systems, candidate generators, features and models that can handle millions of new Pins every day with low latency and effectively distribute fresh content?
    • How to automatically organize new content into Boards so Pinners don’t have to?
    • How to determine what fresh content our Pinners will be inspired by?
    • How to remove biases from existing recommendation systems?
    • How to experiment with and measure the impact of content acquisition changes on the user experience?
  • Be an exemplar for technical quality - design, implementation, documentation, code reviews.
  • Mentor and build capability in your peers across Content Success and sibling teams.

What We're Looking For

  • Languages: Java, Python.
  • Big data processing: Spark, Hive, MapReduce, SQL.
  • Experience with recommender systems or production ML systems.
  • Experience with building large scale distributed systems.
  • Experience as a tech lead of projects with extensive cross-team collaborations.

This position is not eligible for relocation assistance.

At Pinterest we believe the workplace should be equitable, inclusive, and inspiring for every employee. In an effort to provide greater transparency, we are sharing the base salary range for this position. The position is also eligible for equity. Final salary is based on a number of factors including location, travel, relevant prior experience, or particular skills and expertise.

Information regarding the culture at Pinterest and benefits available for this position can be found here.

US based applicants only

$148,049—$304,496 USD

Our Commitment To Diversity

Pinterest is an equal opportunity employer and makes employment decisions on the basis of merit. We want to have the best qualified people in every job. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, protected veteran status, or any other characteristic under federal, state, or local law. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. If you require an accommodation during the job application process, please notify for support.

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