Staff Machine Learning Engineer - User Understanding
Job Description
The User Understanding team develops state-of-the-art models and systems to deeply understand the evolving interests intents and tastes of our 500M+ Pinterest users which power the personalization of Pinterest products across Discovery (Homefeed Search Related Pins) Ads and Growth. As the Staff Machine Learning Engineer of the User Understanding team you will set technical vision lead the team in building next-generation user understanding models and partner cross-functionally to deliver more relevant and personalized experiences to our users.
What you'll do:
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Lead and mentor a team of experienced machine learning engineers in developing advanced user understanding models and systems which are integral to key Pinterest products across Discovery Ads and Growth.
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Collaborate cross-functionally with partners in Product Data Science and Engineering to define strategy set priorities and effectively integrate user insights into core systems and product features.
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Drive experimentation and adoption of new user understanding models with product teams across Pinterest ensuring measurable end-to-end impact on key metrics.
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Manage project execution and stakeholder communication including roadmap planning technical decision-making risk mitigation and progress updates to achieve business goals.
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Provide thought leadership in user modeling and recommender systems by setting a long-term technical vision and advancing the state-of-the-art in the field.
What we’re looking for:
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Hands-on experience developing and deploying large-scale machine learning systems in search recommendation or advertising.
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Demonstrated ML expertise with a proven track record of impactful solutions and a deep understanding of large scale distributed systems.
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6+ years of industry experience in applied machine learning or closely related roles.
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Strong technical leadership including a passion for driving technical direction system architecture and designing robust scalable ML solutions.
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Bachelor’s/Master’s degree in a relevant field such as computer science or equivalent experience.
Relocation Statement:
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This position is not eligible for relocation assistance. Visit our PinFlex page to learn more about our working model.
In-Office Requirement Statement:
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We let the type of work you do guide the collaboration style. That means we're not always working in an office but we continue to gather for key moments of collaboration and connection.
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Date Posted
11/08/2025
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