Engineering Manager (Machine Learning - User Understanding)

Remote Full-time
Requirements
• We’re looking for a leader with deep infrastructure expertise, a passion for personalization and ML-driven experience, and a strong record of delivering ML-enabling platforms at scale,
• 6+ years of industry experience in applied machine learning or closely related roles, with experience developing large-scale machine learning for recommendation or ads systems,
• 2+ years of people management experience leading engineering teams,
• Demonstrated ML expertise with a proven track record of impactful solutions and a deep understanding of large scale distributed systems,
• Strong technical leadership, including a passion for driving technical direction, system architecture, and designing robust, scalable ML solutions

What the job involves
• Pinterest is seeking an Engineering Manager to lead our User Understanding team,
• This team builds and maintains the data and backend systems that drive user modeling, personalization and recommendations—impacting hundreds of millions of users every day,
• You’ll set technical vision, empower a talented group of engineers, and collaborate closely with Machine Learning, Product, and Data Science to unlock better user experiences,
• 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,
• 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,
• Drive experimentation and adoption of new user understanding models with product teams across Pinterest, ensuring measurable end-to-end impact on key metrics,
• Manage project execution and stakeholder communication, including roadmap planning, technical decision-making, risk mitigation, and progress updates to achieve business goals,
• 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,
• Foster a collaborative, inclusive, and high-performing team culture

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