Master's Machine Learning Internship 2026 (USA)

PinterestPalo Alto, CA
92d$11,000 - $11,000

About The Position

As a Machine Learning Intern at Pinterest, you’ll work on tackling new challenges in machine learning and artificial intelligence. Throughout your internship, you’ll join our engineering teams as we maneuver through exponential growth and massive scale while building awesome products and features, creating visually rich experiences, spearheading the discovery problem, and pinpointing tomorrow’s engineering challenges.

Requirements

  • Working towards a Master's degree in Computer Science, ML, NLP, Statistics, Information Sciences or related field
  • 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
  • Strong communicator and team player with the ability to find solutions for open-ended 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

Benefits

  • Meaningful Work: Contribute to projects that impact millions of users worldwide.
  • Mentorship: Learn from and be guided by experienced engineers and researchers in the field.
  • Growth and Development: Participate in professional development workshops and networking events to build your skills and connections.
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