Sr. Manager, Machine Learning Engineering-Applied Research

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At Pinterest, AI isn't just a feature, it's a powerful partner that augments our creativity and amplifies our impact, and we’re looking for candidates who are excited to be a part of that. To get a complete picture of your experience and abilities, we’ll explore your foundational skills and how you collaborate with AI.

Through our interview process, what matters most is that you can always explain your approach, showing us not just what you know, but how you think. You can read more about our AI interview philosophy and how we use AI in our recruiting process here.

We're looking for a highly technical Senior Engineering Manager with a deep understanding of modern recommendation systems to manage, lead and develop a team of ML researchers and engineers within the Applied Science team. In this role, you will lead the strategy of the Recommendation System innovation team. You will help the team build a balanced portfolio of work that addresses both immediate short-term business impact and long-term strategic breakthroughs in areas like Generative Recommendation System (GenRecSys), Large Sequential Models, and Reinforcement Learning (RL). Partnering closely with executive leadership, product management, and engineering partners, you will evolve our technical roadmap and directly drive Pinterest’s core mission forward.

What you will do

Technical Vision and Execution: Own the technical roadmap and strategic vision for Pinterest’s next-generation recommendation systems. Champion the use of state-of-the-art ML techniques to deliver revolutionary innovations in recommendation technology.

Team Leadership & People Management: Support, mentor, and grow a world-class team of Applied Scientists, Machine Learning Engineers, and technical leads. Recruit top talent, foster an inclusive research-to-production culture, and guide career progression.

Portfolio & Strategy Management: Balance execution across two parallel horizons—delivering near-term measurable metric improvements while sponsoring multi-quarter, high-risk/high-reward AI/ML research initiatives.

Research to Production: Successfully transition breakthrough ML research into production-ready systems that directly impact core company metrics.

Cross-functional Partnership: Collaborate seamlessly with Consumer Engineering, Ads Engineering, Platform, Content, and Data Science teams to prototype, build, and scale solutions to complex engineering challenges. Partner with leadership to deepen user understanding and set the strategic direction for our recommendation system roadmap.

What we are looking for

Technical Depth: 7+ years of combined post-graduate academic and industry experience applying state-of-the-art ML technologies to real-world problems on web-scale data, alongside 3+ years of direct people management experience.

Proven Execution: A track record of delivering high-impact initiatives across multiple product areas, with a demonstrated ability to influence peers and leadership using data-driven insights.