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PinterestManager II, Machine Learning – Conversion Visibility
Pinterest operates a visual discovery platform where millions of users find inspiration and creative ideas. To support its advertising ecosystem, the company is hiring a Manager…
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About This Role
Pinterest operates a visual discovery platform where millions of users find inspiration and creative ideas. To support its advertising ecosystem, the company is hiring a Manager II, Machine Learning for its Conversion Visibility team in Seattle. This role is a hybrid position that requires working from the office one day per week, and applicants must live within a commutable distance to the Seattle office. In this capacity, the selected candidate…
Job Description
Pinterest operates a visual discovery platform where millions of users find inspiration and creative ideas. To support its advertising ecosystem, the company is hiring a Manager II, Machine Learning for its Conversion Visibility team in Seattle. This role is a hybrid position that requires working from the office one day per week, and applicants must live within a commutable distance to the Seattle office.
In this capacity, the selected candidate will lead a hybrid team composed of machine learning engineers and backend software engineers. The group focuses on creating end-to-end identity and conversion visibility solutions across serving, modeling, and data infrastructure. This work enables an effective ads marketplace by bridging onsite Pinterest activity with offline conversions while preserving user privacy. The position suits an engineering leader experienced in directing multi-quarter roadmaps and building large-scale machine learning systems in production.
The engineering manager will guide the strategy, execution, and operational excellence of modeling systems used for user match prediction, probabilistic attribution, deduplication, and conversion value prediction. Responsibilities include mentoring team members, establishing engineering best practices, collaborating with product managers and data scientists, and coordinating with other ads teams to integrate solutions smoothly into the broader ecosystem.
Responsibilities
- Attract, hire, mentor, and lead a hybrid team of machine learning and backend software engineers
- Direct the strategy, execution, and operational performance of identity and conversion signal modeling systems
- Partner with product managers and data scientists to define technical strategy and address business needs
- Collaborate with ads ranking, measurement, ingestion, and attribution teams to define interfaces and success metrics
- Set engineering standards for data quality, model evaluation, pipelines, experimentation, and service reliability
- Leverage AI tools to speed up model analysis and architecture iteration while ensuring correctness and reliability
Requirements
- At least 7 years of experience building and deploying large-scale machine learning systems into production
- Minimum 2 years of experience working as an engineering manager or technical lead
- Ability to work on-site in the Seattle office one day per week
Qualifications
- Bachelor Degree in Computer Science, Statistics, or a related technical field, or equivalent experience
- Hands-on experience or familiarity with ads conversion attribution, identity matching, ads ranking, or ads measurement domains
Core Skills
Benefits
- Equity eligibility
Frequently Asked Questions
What is the employment type for this position?
This is a full-time position.
Is remote work allowed for this role?
This is a hybrid position that requires working from the Seattle office one day per week, meaning applicants must live within a commutable distance to that office.
What is the salary range for this role?
The base salary range for US-based applicants is $189,308 to $389,753 USD, and the position is also eligible for equity.
Does this role qualify for relocation assistance?
No, this position is not eligible for relocation assistance.
What educational background is required?
A Bachelor Degree in Computer Science, Statistics, or a related technical field is required, or equivalent experience.
Sample Interview Questions
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