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Sr. Machine Learning Engineer, Monetization Engineering

190k – 332kSan Francisco, CAPalo Alto, CASeattle, WAHybrid2+ YOE
Summary

Develop and evolve machine learning technology stack for Pinterest's Ads monetization, building personalized recommendation systems using deep learning, LLMs, and big data tools. Requires 2+ years ML experience in recommender systems, ranking, and large-scale systems.

About the role

What you’ll do:

  • Build cutting edge technology using the latest advances in deep learning and machine learning to personalize Pinterest
  • 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
  • Use data driven methods and leverage the unique properties of our data to improve candidates retrieval
  • Work in a high-impact environment with quick experimentation and product launches
  • Keep up with industry trends in recommendation systems
  • Leverage LLMs to enhance content understanding

What we’re looking for:

  • 2+ years of industry experience applying machine learning methods (e.g., user modeling, personalization, recommender systems, search, ranking, natural language processing, reinforcement learning, and graph representation learning)
  • Degree in computer science, statistics, or related field; or equivalent experience
  • End-to-end hands-on experience with building data processing pipelines, large scale machine learning systems, and big data technologies (e.g., Hadoop/Spark)
  • Practical knowledge of large scale recommender systems, or modern ads ranking, retrieval, targeting, marketplace systems

Nice to have:

  • M.S. or PhD in Machine Learning or related areas
  • Publications at top ML conferences
  • Expertise in scalable realtime systems that process stream data
  • Passion for applied ML and the Pinterest product
  • Background in computational advertising
Skills
Machine LearningDeep LearningRecommender SystemsNatural Language ProcessingReinforcement LearningGraph Representation LearningSparkHadoopLLMsBig Data
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