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Master's Machine Learning Internship 2026 (USA)

Pinterest

$11,000 - $11,000
Sep 22, 2025
San Francisco, CA, US • Palo Alto, CA, US • Seattle, WA, US • New York, NY, US
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Pinterest Machine Learning interns help build personalized experiences to help Pinners create a life they love. With just over 3,000 global employees, our teams are small, mighty, and still growing. At Pinterest, you’ll experience hands-on access to an incredible vault of data and contribute large-scale recommendation systems in ways you won’t find anywhere else.

Requirements

  • Machine Learning (ranking, computer vision, NLP, content recommendations, embedding, information retrieval etc)
  • Experience with big data technologies (e.g., Hadoop/Spark) and scalable realtime systems that process stream data
  • Proficiency in at least one systems language (Java, C++, Python) or one ML framework (Tensorflow, Pytorch, MLFlow)
  • Experience in research and in solving analytical problems

Responsibilities

  • Lead your own project start to finish to contribute in cutting-edge research in machine learning and artificial intelligence that can be applied to Pinterest problems
  • Collect, analyze, and synthesize findings from data and build intelligent data-driven models
  • Write clean, efficient, and sustainable code
  • Use machine learning, natural language processing, and graph analysis to solve modeling and ranking problems across discovery, ads and search
  • Scope and independently solve moderately complex problems
  • Demonstrate accountability for the quality and completion of your tasks and projects, collaborating with your team and seeking guidance as needed

Other

  • Working towards a Master's degree in Computer Science, ML, NLP, Statistics, Information Sciences or related field
  • Strong communicator and team player with the ability to find solutions for open-ended problems
  • Internships are 12 weeks paid, with fixed start dates in May or June to accommodate varying school calendars.
  • Depending on the team, our summer internships will be located either remote or hybrid in San Francisco, Palo Alto, New York or Seattle offices.
  • US based applicants only