Director, Machine Learning Engineering, Programmatic Ads

Pinterest is one of the fastest growing online ad platforms, and our success depends on mining rich user interest data that helps us connect users with highly relevant advertisers/ products. We’re looking for a leader with experience in machine learning, data mining, and information retrieval to lead a team that develops new data-driven techniques to show the most engaging and relevant promoted content to the users. You’ll be leading a world-class ML team that is growing quickly and laying the foundation for Pinterest’s business success.

What you’ll do:

• Manage and grow the engineering team, providing technical vision and long-term roadmap
• Design and implement algorithms for real-time bidding, ad scoring/ranking, inventory selection and yield optimization on the DSP
• Hire, mentor and grow a team of engineers. Set technical direction, manage project roadmaps, and actively guide team execution. Collaborate across Product, Engineering, Marketing and Sales – translating business goals into ML requirements and ensuring solutions meet cross-functional needs
• Product strategy and advocacy. Define and evangelize the ML roadmap for programmatic products. Present findings and roadmaps to senior leadership, and work with stakeholders to align analytics projects with company goals (e.g. privacy-first personalization, new DSP features)
  

What we’re looking for:

• M.S/ PhD degree in Computer Science, Statistics or related field
• 10+ years of industry experience building production machine learning systems at scale, data mining, search, recommendations, and/or natural language processing
• Experience in programmatic advertising or information retrieval contexts (RTB, DSP/SSP, search). Familiarity with ad campaign metrics, auction mechanics and yield optimization
• Excellent at cross-functional collaboration and stakeholder communication

Relocation Statement:

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

In-Office Requirement Statement:

• 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 per month and therefore needs to be in a commutable distance from one of the following offices: San Francisco, Palo Alto, Seattle, Los Angeles.

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