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Manager II – Machine Learning Engineering – Search Ranking & Blending

Manager II – Machine Learning Engineering – Search Ranking & Blending

CompanyPinterest
LocationSan Francisco, CA, USA
Salary$176924 – $364254
TypeFull-Time
DegreesMaster’s, PhD
Experience LevelSenior, Expert or higher

Requirements

  • MS or PhD degree in Computer Science, Machine Learning, Statistics or related field, or equivalent experience.
  • Proven experience in leading and managing large-scale production systems, such as search, recommendation, or advertising platforms, utilizing advanced machine learning and big data technologies.
  • Strong background in applied machine learning; familiarity with recommendation systems is highly desirable.
  • Demonstrated ability to define and drive the strategic roadmap for scalable, production-quality systems from concept to execution.
  • Strong focus on product impact and user experience within a consumer-focused environment.
  • Minimum of 2 years of experience managing a high-performing machine learning engineering team of 8+ members.
  • 8+ years of experience in software development, with a proven track record of delivering impactful solutions.

Responsibilities

  • Be responsible for the search ranking and blending area, a significant component of the search product at Pinterest.
  • Deeply understand the Pinterest search product and drive the vision for the search ranking and blending team, ensuring the team’s work directly contributes to the company’s goals.
  • Manage and mentor a team of Machine Learning engineers, providing guidance and support to help them grow their careers.
  • Collaborate closely with other engineering teams at Pinterest to enhance the search experience for users, including Search Product, Infrastructure, research, and content signals.
  • Provide visibility to senior leadership regarding the team’s impact.
  • Partner with stakeholders across the company, including product management, data scientists, and design, to expand impact.
  • Build a culture of excellence and expertise within the team.

Preferred Qualifications

  • Familiarity with recommendation systems is highly desirable.