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Master's Data Science Internship 2027 (USA)
A 12-week paid summer 2027 internship for Master's students on Pinterest's data science teams: analyzing user behavior, designing core metrics and A/B experiments, and applying statistical modeling with SQL and Python/R alongside product and engineering partners.

Master's Machine Learning Internship 2027 (USA)
A 12-week paid summer internship (May or June 2027 start) for Master's students to lead an end-to-end ML/AI project at Pinterest, working on large-scale recommendation systems and full-stack production ML — from research and data engineering to training and inference — while leveraging AI agents for prototyping and code validation.

Master's University Grad Data Scientist (USA)
New-grad (master's level) Data Scientist at Pinterest working across multiple data science teams: analyzing large-scale user data, designing core metrics, and designing/evaluating A/B experiments to guide product decisions. Core tools are SQL, Python or R, statistical modeling, and machine learning.

PhD Data Science Internship 2027 (USA)
A 12-week paid summer internship for PhD students on Pinterest's data science teams in 2027. Interns analyze user and advertiser behavior, design core metrics and A/B experiments, and apply statistical modeling, SQL and Python/R while partnering with product, engineering and design.

Machine Learning Engineer, Core Engineering
Build and improve large-scale machine learning systems to personalize Pinterest’s recommendation feeds, ads, and search using deep learning and big data tools.

Sr. Machine Learning Engineer, Core Engineering
Senior Machine Learning Engineer at Pinterest building personalized recommendation systems using deep learning and large-scale data pipelines to enhance user experiences across Homefeed, Ads, and Search.

Machine Learning Engineer, Evaluation and Quality, Creativity Apps
ML engineer on Apple's Creativity Apps team in San Diego who owns evaluation and quality of AI features: defining eval strategy and metrics, curating datasets, building evaluation infrastructure, and driving model-to-ship quality decisions. Core tech: Python and/or Swift, LLMs, and agentic workflows.