The Notifications Content Science team directly contributes to the company’s top line growth (MAUs) by recommending personalized, high quality, inspirational content to Pinners through Email, Push and In-app Notifications. The team focuses on minimizing user churn by recommending engaging and contextual content that continuously gives Pinners a compelling reason to return to Pinterest. This is accomplished through:

• Designing, building and maintaining the ML components for Retrieving, Ranking and Blending content that powers our Email, Push and In-app Notifications. 

• Ensuring that the content is personalized, inspirational and embodies the Pinterest values.

What you’ll do

• Tackle various challenging problems, including Candidate Retrieval, Ranking, Utility and Blending. This involves recognizing opportunities, researching, building, improving, testing and productionizing ML models with the goal to improve pinner satisfaction and reduce churn.

• Be a strong builder that can productionize a new ML component (e.g. a new retrieval source, a light-weight L1 ranker, a complex L2 ranker) end-to-end. 

• Have the ability to break down a large, ambiguous project into well defined tasks and mentor ICs towards executing them. 

• Work closely with the Engineering and Product leads to craft a compelling, ambitious and impactful AI/ML-powered technical strategy for evolving Notifications Content at Pinterest.

• Translate the technical strategy for Notifications Content into a concrete engineering roadmap and lead the team’s technical execution towards realizing the vision.

What we’re looking for:

• 5+ years of hands-on professional experience in designing and building end-to-end large scale candidate retrieval and ranking ML models (e.g. Feed, Search, Ads Recommendations). 

• 1+ years of experience with developing technical strategy for one or more AI/ML-powered core product teams (e.g. Growth, Search, Ads etc.).

• Bachelor’s/Master’s degree in a relevant field such as computer science, or equivalent experience.

• Deep systems level understanding of industry scale recommendation systems.

• Proficient in programming languages such as Python and building ML models using PyTorch or Tensorflow

• Excellent track record of collaborating with strong Engineering (EMs, TLs and Senior ICs) and Cross-functional Stakeholders (PMs, Data Scientists, Designers and PMMs) to influence the team’s 6 - 12 month engineering strategy.

This position is not eligible for relocation assistance.

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