Director of Machine Learning Engineering (Content & User Understanding)
full-remoteleadpermanentbackenddataengineering-management Full remote 9 days ago via WTTJ
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Machine LearningDeep LearningLLMVLMRecommendation SystemsAdsSearchPeople LeadershipBackend EngineeringModel Serving
About the role
Role overview
Pinterest is hiring a Director of Machine Learning Engineering (Content & User Understanding) to lead the Content and User Understanding ML team. You will set the long-term ML/AI vision and technical strategy, and drive execution for company-wide models and systems that improve how Pinterest understands content and users.
Responsibilities
- Define the long-term ML/AI vision and technical strategy for content and user understanding models and systems.
- Lead execution to build and scale ML/AI systems across Pinterest.
- Oversee multiple teams of machine learning and backend engineers/managers.
- Collaborate with Product, Engineering, and Data Science leaders to translate foundational ML techniques into measurable business impact.
- Manage, hire, and develop managers and ML/backend engineers.
- Foster a culture of innovation, technical excellence, rigor, and impact.
Requirements
- Proven success as a people leader for complex ML organizations, including managing managers and strong communication/influence across partner teams.
- Deep ML expertise building and operating large-scale ML systems, particularly in recommendation, ads, or search.
- 12+ years of professional experience as a technical leader, with 5+ years in people leadership roles.
- Track record of setting long-term technical vision and delivering top-line business impact.
- Technical degree in a related field, or equivalent practical experience.
Nice to have / preferred signals
- Expertise in large-scale deep learning, including VLM and LLM approaches.
About Pinterest
Pinterest is a consumer internet company focused on helping people discover and explore ideas through content. It operates in the social media and advertising ecosystem, relying on large-scale machine learning to improve content relevance and user understanding.
Scraped 6/11/2026