Sr. Manager, Machine Learning Engineering-Applied Research

About the Role

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, building a balanced portfolio that addresses short-term business impact and long-term strategic breakthroughs in areas like Generative Recommendation Systems (GenRecSys), Large Sequential Models, and Reinforcement Learning (RL).

What You Will Do

• Technical Vision and Execution: Own the technical roadmap and strategic vision for Pinterest’s next-generation recommendation systems. Champion state-of-the-art ML techniques to deliver 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 and foster an inclusive research-to-production culture.
• Portfolio & Strategy Management: Balance 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 with Consumer Engineering, Ads Engineering, Platform, Content, and Data Science teams to prototype, build, and scale solutions.

What We Are Looking For

• 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.
• 3+ years of direct people management experience.
• Track record of delivering high-impact initiatives across multiple product areas with data-driven insights.
• Experience mentoring, coaching, and up-leveling software and machine learning engineers.
• Continuous learner with an appetite for building proof-of-concept prototypes.
• Ability to transform ambiguous questions into well-defined projects with clear success metrics.
• Excellent communication skills backed by a strong track record of publications in machine learning, AI, data science, or related technical fields.
• B.S. in Computer Science, ML, NLP, Statistics, Information Sciences, or related field.

Preferred Qualifications

• Experience managing hybrid teams of research-oriented scientists and production-focused machine learning engineers.
• Track record of publishing at top-tier ML/RecSys conferences (KDD, RecSys, NeurIPS, CVPR).
• Familiarity with generative AI for recommendations (e.g., semantic indexing, LLMs/GenRec architectures) or deep RL for long-term user value optimization.
• Experience leveraging modern LLM/Agentic workflows and generative AI.

Work Arrangement

• This role can be situated anywhere in the US, with an in-office requirement for in-person collaboration 1-2 times per quarter.