Manager Ii, Machine Learning-search

Pinterest Pinterest · Consumer · Palo Alto, CA · Core Engineering

Manager II, Machine Learning-Search at Pinterest, leading a team responsible for major areas of the search engine, including indexing, ranking, query understanding, personalization, ML-based retrieval, shopping, videos, and infrastructure efficiency. The role involves innovative applications of NLP and Vision Models for query recommendations, multimodal search, agentic search, and query-based module generation. Requires experience leading large-scale production ML systems and applied ML experience.

What you'd actually do

  1. The candidate will be responsible for major areas of the search engine for more than 450 million monthly active Pinterest users, including indexing and document ranking, query and content understanding, personalization, ML based retrieval, shopping, videos, as well as infrastructure efficiency and scalability.
  2. In addition, the candidate will work on innovative applications of NLP and Vision Models, and other techniques to drive query recommendations, multimodal search, agentic search, multimodal query understanding, and query based module generation and ranking.
  3. Work closely with the other engineering teams in Pinterest to bring superior search experience to our users, such as Search Product, Infrastructure, research and content signals.
  4. Deeply understand the Pinterest search product, and drive the vision for the team.
  5. Mentor and grow managers, leaders and engineers on the team.

Skills

Required

  • Experience leading and working on a large-scale production search, recommendation or ads systems that are based on state-of-the-art machine learning and big data technology.
  • Ability to drive the roadmap and directions of scalable production quality systems end-to-end.
  • A knack for product and impact on users of a consumer product.
  • 3+ years of experience in leading/managing a highly impactful ML-based engineering team of 5+ size; 7+ years of software development experience.
  • Bachelors degree in computer science or related technical field, or equivalent experience

Nice to have

  • Applied machine learning experience is strongly preferred.
  • Experience in related fields such as recommendation systems, natural language processing and computer vision is a bonus.
  • 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

  • large-scale production search, recommendation or ads systems
  • state-of-the-art machine learning
  • big data technology
  • applied machine learning
  • NLP
  • computer vision
  • multimodal search
  • agentic search

Other signals

  • large-scale production search, recommendation or ads systems
  • state-of-the-art machine learning
  • big data technology
  • applied machine learning
  • NLP
  • computer vision
  • multimodal search
  • agentic search