Build and improve large-scale ML models for personalization and recommendation across Pinterest surfaces including Shopping. Requires 5+ years applying ML methods and experience with big data pipelines.
Salary not listed
Remote5+ YOEML Engineering
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)
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
What we’re looking for:
5+ 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)
End-to-end hands-on experience with building data processing pipelines, large scale machine learning systems, and big data technologies (e.g., Hadoop/Spark)
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
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
Skills
Deep LearningMachine LearningRecommender SystemsPersonalizationNatural Language ProcessingReinforcement LearningGraph Representation LearningHadoopSparkData Processing Pipelines
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