Manager Ii, Machine Learning-content Success

Pinterest Pinterest · Consumer · San Francisco, CA · Core Engineering

Manager II, Machine Learning-Content Success at Pinterest. This role leads and mentors a team of backend and machine learning engineers to develop advanced signals, integrations, and systems for recommendation surfaces (Homefeed, Search, Related Pins, Ads) impacting discovery, ads, and growth. The manager provides technical vision for content distribution and recommender systems, manages project execution, and stakeholder communication.

What you'd actually do

  1. Lead, mentor and grow a team of experienced backend and machine learning engineers in developing advanced signals, integrations and systems, which are integral to key Pinterest products across Discovery, Ads, and Growth.
  2. Provide thought leadership in content distribution and recommender systems by setting a long-term technical vision and advancing the state-of-the-art in the field. Act as the glue between content acquisition and recommendation pods becoming the expert in both these areas.
  3. Manage project execution and stakeholder communication, including roadmap planning, technical decision-making, risk mitigation, and progress updates to achieve business goals.

Skills

Required

  • 7+ years of industry experience
  • 2+ years of management experience
  • Experience building and leading high performing teams within a visible business vertical
  • Experience working with numerous cross functional partners to drive a collective initiative
  • Bachelors degree in a technical field, or equivalent work experience
  • 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

What the JD emphasized

  • advanced signals
  • integrations
  • systems
  • content distribution
  • recommender systems

Other signals

  • recommendation systems
  • content distribution
  • machine learning engineers
  • advanced signals
  • integrations
  • systems