Pinterest

Principal Machine Learning Engineer, Ads Delivery

$315K–$551KFull-time · San Francisco, CA +2 more
✓ Verified live on the employer's own system · added 320 days ago
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Senior · 10+ yrs exp

Requirements

Experience: 10+ years

Skills & tools

Statistical AnalysisOperationsMachine LearningProgrammingTroubleshootingRecordkeepingSQL
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Full job description

Within the Ads Delivery team, we try to connect the dots between the aspirations of pinners and the products offered by our partners. In this role, you will be responsible for developing and executing a vision for the evolution of the Pinterest marketplace. You will design and implement systems that improve the ads delivery funnel, experiments that shape the utility function, auction mechanism design, ad allocation and for deriving new insights through analysis of the marketplace dynamics.

In short, this is a unique position, where you’ll get the freedom to work to bring together pinners and partners in this unique marketplace.

  • Build and improve backend systems and statistical models that underlay the marketplace to maximize value for Pinners, Partners and Pinterest.
  • Define and implement experiments to understand long term Marketplace effects.
  • Develop strategies to balance long and short term business objectives.
  • Drive multi-functional collaboration with peers and partners across the company to improve knowledge of marketplace design and operations.
  • Degree in Computer Science, Machine Learning, Statistics or related field.
  • 10+ years of professional experience as a hands-on engineer and technical leader leading multiple projects.
  • Strong software engineering and mathematical skills with knowledge of statistical methods.
  • Hands-on experience with large-scale online e-commerce systems is a plus.
  • Experience using Cursor, Copilot, Codex, or similar AI coding assistants for development, debugging, testing, and refactoring
  • Familiarity with LLM-powered productivity tools for documentation search, experiment analysis, SQL/data exploration, and engineering workflow acceleration
  • We let the type of work you do guide the collaboration style. That means we're not always working in an office, but we continue to gather for key moments of collaboration and connection.
  • This role will need to be in the office for in-person collaboration 1-2 times/month , and therefore needs to be in a commutable distance from one of the following offices: San Francisco, Palo Alto, Seattle.

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