Engineering Manager, Personalization at Pinterest
San Francisco, CA, US

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. As a Pinterest employee, 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 users make their lives better in the positive corner of the internet.

The personalization team builds cutting edge user understanding models and systems to deeply understand the evolving interests, intents and tastes of our 350m+ users, which is one of the most essential ML components powering Pinterest products across Discovery (Homefeed, Search, Related Pins), Ads, Shopping and Growth. As the engineering manager of the personalization team, you’ll set technical vision and lead the team to build the next generation user understanding models and systems, and work with many cross functional partners to deliver more relevant and delightful results to our Pinners.

What you’ll do:

  • Lead a team of experienced ML engineers to build cutting edge user understanding models and systems, which are widely incorporated in Pinterest products across Discovery (Homefeed, Search, Related Pins), Ads, Shopping and Growth
  • Partner closely with vertical teams across Pinterest to experiment new ML models / systems and deliver end-to-end metric impact
  • Be a thought leader on user modeling and recommender systems, set and execute technical vision, and improve state-of-the-art technology

What we’re looking for:

  • 8+ years of machine learning engineering or applied research experience
  • 2+ years of people management experience
  • Knowledgeable experience working on machine learning areas related to recommendation systems or ads
  • Ideal but not required:
    • PhD in Machine Learning and related fields
    • Publications, blog posts, or tech talks on topics of machine learning at top AI/ML conferences
    • Experience working with cross-functional teams on collaboration projects