Manager Ii, Machine Learning Engineering, Core Engineering

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

Manager II, Machine Learning Engineering for Core Engineering at Pinterest, focusing on search and recommendations for over 500 million users. The role involves leading a team of ML engineers, driving technical direction, strategic planning, and execution for large-scale, low-latency systems and state-of-the-art ML models that deliver significant impact to pinners and business metrics.

What you'd actually do

  1. Be responsible for major areas of search, recommendations, notifications, etc for more than 500 million monthly active Pinterest users. Potential areas of impact include ML based retrieval, multi domain ranking, L1 modeling, candidate generators, sequence modeling, relevance modeling, and infrastructure efficiency and scalability
  2. Deeply understand the Pinterest product and drive the vision for the team, ensuring the team’s work directly contributes to the company’s goals
  3. Manage and mentor a team of Machine Learning engineers (L13 - L16), providing technical guidance and support to help them grow their careers. Identify team needs and hire strong candidates
  4. Collaborate closely with other engineering teams at Pinterest to enhance the experience for users, including Advanced Technology Group, Infrastructure, Content Understanding and User Understanding
  5. Provide visibility to senior leadership regarding the team’s global impact

Skills

Required

  • MS/PhD in Computer Science, ML, NLP, Statistics, Information Sciences, related field, or equivalent experience
  • Experience leading and working on a large-scale production recommendation, e-commerce, search or ads systems that are based on state-of-the-art machine learning and big data technology
  • Strong experience in related fields such as recommendation systems and applied machine learning experience is required.
  • 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 1 year of experience managing a high-performing machine learning engineering team of 10+ members
  • 8+ years of experience in software development, with a proven track record of delivering impactful solutions

Nice to have

  • Natural language processing
  • computer vision
  • Experience with 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 recommendation
  • state-of-the-art machine learning
  • applied machine learning experience is required

Other signals

  • recommendation systems
  • large-scale systems
  • machine learning models
  • product impact
  • user experience