Manager II, Machine Learning Engineering Content Foundation
Quick summary
- Work type
- Remote
- Location
- Remote
- Salary
- $222,716–$389,753 / yr
- Posted
- 2 days ago
- Freshness
- Confirmed live yesterday
Market check
Salary context
How this pay compares to similar roles
This role pays more than 92% of similar roles. Most pay $192,050–$254,750 — the shaded band above. At the midpoint, this role pays about $306k versus about $223k 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 48 open roles on FindRole.
Listed pay typically runs $177,185–$339,078 across 42 roles with salary data.
Most-posted roles
- Machine Learning Engineer 7
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At a glance
TL;DR · Manager II, Machine Learning Engineering Content Foundation
Manager II, Machine Learning Engineering-Content Foundation joins the Content Foundation ML team to lead a group of engineers and applied scientists in developing foundational content understanding signals. This role involves setting long-term technical visions for semantic signal generation and building scalable infrastructure that powers Discovery, Search, Growth, and Ads. The manager will oversee project execution, roadmap planning, and stakeholder communication while solving complex challenges regarding inference throughput, serving efficiency, and the integration of LLM and VLM technologies to capture content richness. Key requirements include experience with large-scale distributed training, Hadoop, Spark, and GenAI models for recommendation systems. The role focuses on creating reusable foundational layers like captions and summaries to improve personalization and engagement while ensuring high signal quality across multiple locales through robust monitoring and evaluation systems.
Skills
What you'll do
- Lead, mentor, and grow a team of engineers and applied scientists developing content understanding signals and infrastructure.
- Establish the long-term technical vision for semantic signal generation and scalable model-powered infrastructure.
- Manage project execution including roadmap planning, technical decision-making, risk mitigation, and stakeholder communication.
- Leverage LLM and VLM technologies to extract high-quality semantic information from Pinterest content across multiple locales.
- Build reusable foundational layers like captions and summaries to power multiple downstream use cases efficiently.
- Optimize inference throughput, freshness, and serving efficiency for millions of daily pieces of content.
- Develop robust monitoring, evaluation, and debugging systems to ensure signal quality and performance at scale.
- Partner with cross-functional teams to align technical roadmaps with business goals in discovery, search, growth, and ads.
What we're looking for
- 7+ years of industry experience including at least 2 years of management experience.
- Master's degree in computer science, computer engineering, or equivalent work experience.
- Publication record at top machine learning and data mining conferences such as NeurIPS, ICML, KDD, or SIGIR.
- Experience with large scale distributed training and inference of LLM and VLM models.
- Experience with distributed tooling for ML data pipelines like Hadoop or Spark.
- Experience leading ambiguous ML projects to build and improve GenAI models for content understanding and recommendation systems.
- Proven technical leadership in both ML and Data systems, including setting multi-quarter roadmaps and aligning stakeholders on priorities.
- Excellent cross-functional communication skills to collaborate with product, data science, and partner ML teams.
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