Sr. Machine Learning Engineer, Monetization Engineering

Pinterest Pinterest · Consumer · San Francisco, CA · Monetization

Machine Learning Engineer focused on personalization and monetization within the consumer domain, specifically for Pinterest's ad platform. The role involves building and improving ML models for various product surfaces, leveraging data for candidate retrieval, and enhancing content understanding with LLMs. It requires end-to-end experience with ML systems and a practical understanding of recommender systems or ad ranking.

What you'd actually do

  1. Build cutting edge technology using the latest advances in deep learning and machine learning to personalize Pinterest
  2. Partner closely with teams across Pinterest to experiment and improve ML models for various product surfaces (Homefeed, Ads, Growth, Shopping, and Search), while gaining knowledge of how ML works in different areas
  3. Use data driven methods and leverage the unique properties of our data to improve candidates retrieval
  4. Work in a high-impact environment with quick experimentation and product launches
  5. Keep up with industry trends in recommendation systems
  6. Leverage LLMs to enhance content understanding

Skills

Required

  • deep learning
  • machine learning
  • personalization
  • recommender systems
  • search
  • ranking
  • natural language processing
  • reinforcement learning
  • graph representation learning
  • data processing pipelines
  • large scale machine learning systems
  • big data technologies
  • Hadoop
  • Spark
  • ads ranking
  • retrieval
  • targeting
  • marketplace systems
  • LLMs

Nice to have

  • M.S. or PhD in Machine Learning or related areas
  • Publications at top ML conferences
  • Cursor
  • Copilot
  • Codex
  • LLM-powered productivity tools
  • scalable realtime systems
  • stream data processing
  • applied ML
  • computational advertising

What the JD emphasized

  • 2+ years of industry experience applying machine learning methods
  • End-to-end hands-on experience with building data processing pipelines, large scale machine learning systems, and big data technologies
  • Practical knowledge of large scale recommender systems, or modern ads ranking, retrieval, targeting, marketplace systems

Other signals

  • personalization
  • recommendation systems
  • ads ranking
  • LLMs