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Manager II, Machine Learning Engineering, Ads Identity Modeling
Manager II, Machine Learning Engineering, Ads Identity ModelingPinterest • San Francisco, CA, US
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Manager II, Machine Learning Engineering, Ads Identity Modeling

Manager II, Machine Learning Engineering, Ads Identity Modeling

Pinterest • San Francisco, CA, US
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  • [job_card.full_time]
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Manager II, Machine Learning Engineering, Ads Identity Modeling

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Millions of people around the world come to our platform to find creative ideas, dream about new possibilities and plan for memories that will last a lifetime. At Pinterest, we're on a mission to bring everyone the inspiration to create a life they love, and that starts with the people behind the product.

Ads Identity Modeling (AIM) sits within the Ads Conversion Modeling group in the Ads Performance org and focuses on identity and conversion modeling that improves conversion ads performance and unlocks new optimization objectives in close partnership with Ads Measurement and ranking teams. We treat conversion data as first-class : growing resilient conversion signals and amplifying their usage across Pinterest to drive measurable impact in ads delivery and beyond. The team owns core identity and conversion-linked ML systems, including User Match Prediction (UMP), and is also responsible for building models that focus on driving incremental conversions.

What You'll Do

Lead the roadmap and technical direction for User Match Prediction (UMP)—from features and training data to model deployment—to increase match rate / quality and strengthen downstream attribution and optimization.

Define and productionize a model to generate a user match confidence score, and use it to optimize label weighting and feature construction in conversion models (e.g., oCPM / ROAS).

Develop and ship models that increase incremental conversions, partnering with Data Science and Product to set success criteria and measurement plans.

Partner with Ads Measurement, Ads Signals, Ranking, and ML Infra to translate identity improvements into reliable online impact and strong operational readiness.

Guide model architecture evolution (e.g., feature interactions, multi-task learning, serving freshness) and iterate on UMP initiatives that expand coverage and resilience (CAPI, WAU attribution, IP-loss mitigation).

Contribute to the longer-term Identity Graph (IDG) collaboration (multi-hop identifiers, candidate generation and ranking) to improve identity resolution and downstream utility.

Hire, mentor and grow ML engineers in ads quality and partner teams and help to uplevel ML talent across the company.

What We're Looking For

MS or PhD degree in Computer Science, Machine Learning, Statistics or related field.

6+ years of industry experience with related background in Ads conversion modeling / products or Ads measurement modeling / science.

2+ years of experience as TLM or EM managing an engineering or applied science team.

Strong software engineering and mathematical skills with knowledge of machine learning.

In-Office Requirement Statement

We let the type of work you do guide the collaboration style. That means we're not always working in an office, but we continue to gather for key moments of collaboration and connection.

This role will need to be in the office for in-person collaboration once a week and therefore needs to be in a commutable distance from one of the following offices : San Francisco / Palo Alto / Seattle.

Relocation Requirement Statement

This position is not eligible for relocation assistance.

At Pinterest we believe the workplace should be equitable, inclusive, and inspiring for every employee. In an effort to provide greater transparency, we are sharing the base salary range for this position. The position is also eligible for equity. Final salary is based on a number of factors including location, travel, relevant prior experience, or particular skills and expertise.

US based applicants only.

Salary : $208,145—$364,254 USD

Our Commitment To Inclusion

Pinterest is an equal opportunity employer and makes employment decisions on the basis of merit. We want to have the best qualified people in every job. All qualified applicants will receive consideration for employment without regard to race, color, ancestry, national origin, religion or religious creed, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender, gender identity, gender expression, age, marital status, status as a protected veteran, physical or mental disability, medical condition, genetic information or characteristics (or those of a family member) or any other consideration made unlawful by applicable federal, state or local laws. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. If you require a medical or religious accommodation during the job application process, please complete this form for support.

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