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Staff Machine Learning Engineer, Creative Optimization

  • San Francisco, California, United States / Palo Alto, California, United States / Seattle, Washington, United States
  • Engineering
  • Regular
We're Hiring 1X1


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 is a visual platform. Within the Creative Optimization team, we work to bring Pinterest’s computational photography technologies to Ad creative and deliver actionable and personalizable ads to drive performance on the platform at scale.

What you’ll do:

  • Be responsible for the development of cutting edge applied machine learning products within high-performance, scalable ML systems.
  • Identify opportunities from existing systems and design innovative solutions to enhance and optimize creative performance.
  • Develop and optimize the Machine Learning models that leverage user engagement signals to enhance ad creative visual and content.
  • Work closely with XFN engineering teams to drive large efforts across different systems.
  • Be an owner and lead the full cycle of product, collaborating closely with product and sales teams to align requirements and drive new products from conception to design and implementation.
  • Demonstrate tech leadership to develop ML best practices and influence team culture.

What we’re looking for:

  • Degree in Computer Science, Statistics or related field
  • Experience building production machine learning systems at scale, data mining, recommendations, optimization, and/or computer vision
  • Experience leading projects from scratch.
  • Experience in mentoring junior members on the team and drive cross-functional collaboration.
  • Strong mathematical skills with knowledge of statistical methods
  • Background in computational photography is a plus, but not required

Relocation Statement:

This position is not eligible for relocation assistance. Visit our PinFlex page to learn more about our working model.


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—$258,822 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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