Senior Manager, Machine Learning Engineering-Applied Research
Quick summary
- Work type
- Remote
- Location
- San Francisco, CA
- Salary
- $227,871–$469,147 / yr
- Posted
- 18 days ago
- Freshness
- Confirmed live today
- Nearby
- 99+ roles within 25 mi
Market check
Salary context
How this pay compares to similar roles
This role pays more than 98% of similar roles. Most pay $208,743–$260,866 — the blue band above. At the midpoint, this role pays about $349k versus about $235k for comparable roles.
Based on 240 similar postings.
Employer
About Pinterest
Pinterest is a visual discovery and inspiration platform where people find ideas for home, style, recipes, and more. It serves hundreds of millions of users worldwide through its image and video pinboard product.
Pinterest currently has 76 open roles on FindRole.
Listed pay typically runs $177,185–$339,078 across 70 roles with salary data.
Most-posted roles
- Software Engineer 17
- Machine Learning Engineer 14
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At a glance
TL;DR · Senior Manager, Machine Learning Engineering-Applied Research
The Sr. Manager, Machine Learning Engineering-Applied Research will lead a team of ML researchers and engineers within the Applied Science team. This leadership role involves managing the technical roadmap and strategic vision for next-generation recommendation systems. The manager will oversee a portfolio of work balancing immediate business impact with long-term research in Generative Recommendation Systems, Large Sequential Models, and Reinforcement Learning. Key responsibilities include mentoring staff, recruiting talent, and transitioning breakthrough research into production-ready systems. The role requires expertise in state-of-the-art ML technologies, web-scale data, and LLM or agentic workflows. Candidates must possess an MS/PhD in a relevant field and demonstrate experience with semantic indexing and deep RL to solve complex engineering challenges across consumer, ads, and platform domains.
Skills
What you'll do
- Own the technical roadmap and strategic vision for next-generation recommendation systems.
- Mentor and grow a team of Applied Scientists, Machine Learning Engineers, and technical leads.
- Balance short-term business metric improvements with long-term high-risk AI/ML research initiatives.
- Transition breakthrough ML research into production-ready systems that impact core company metrics.
- Collaborate with cross-functional engineering and data science teams to prototype and scale solutions.
- Translate ambiguous business questions into well-defined projects with clear success metrics.
- Champion the use of state-of-the-art ML techniques like GenRecSys and Reinforcement Learning.
What we're looking for
- MS/PhD in Computer Science, ML, NLP, Statistics, Information Sciences, or a related field.
- 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.
- Proven track record of delivering high-impact initiatives across multiple product areas using data-driven insights.
- Experience mentoring, coaching, and up-leveling software and machine learning engineers.
- Excellent communication skills with a strong track record of publications in machine learning, AI, data science, or related technical fields.
- Experience managing hybrid teams of research-oriented scientists and production-focused machine learning engineers (preferred).
- Track record of publishing at top-tier ML/RecSys conferences (KDD, RecSys, NeurIPS, CVPR) (preferred).
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