Director, Machine Learning Engineering, Ads Measurement

Pinterest•San Francisco, WA

1d•Hybrid

About The Position

Pinterest is looking for a strategic and experienced engineering leader to define the technical direction for Pinterest’s advertiser measurement and signal-quality ecosystem. In this role, you’ll lead managers and senior technical leaders across Interfaces, Ingestion, User Match, and Conversion Quality, driving multi-year investments in machine learning, data platforms, experimentation, privacy, and production reliability. You’ll partner closely with Product, Data Science, Ads Quality, Infrastructure, Privacy, Legal and Sales to translate complex advertiser and business challenges into scalable solutions—and build an inclusive, high-performing organization equipped to deliver measurable impact at scale.

Requirements

Strong background ads measurement, identity, signals and large-scale data processing.
Experience leading an engineering organization through managers and senior technical leaders.
Demonstrated ability to define and execute technical strategy across multiple teams.
Experience operating systems with demanding scale, reliability, privacy, and data-quality requirements.
Track record of improving organizational execution, developing leaders, and creating distributed ownership.
Exceptional analytical thinking and ability to move from ambiguous business problems to measurable technical outcomes.
Strong executive communication and cross-functional influence.
Exceptional analytical thinking and ability to move from ambiguous business problems to measurable technical outcomes.
Strong executive communication and cross-functional influence.
Bachelor’s degree in a relevant field such as computer science, statistics, machine learning, or equivalent experience.

Nice To Haves

Experience leading through major privacy, browser, platform, or signal-availability changes.
Ads optimization, or privacy-enhancing technologies.
Probabilistic matching, graph systems, anomaly detection, event-quality modeling, or confidence scoring.
ML platforms, real-time or streaming systems, large-scale experimentation, and model governance.
Experience applying AI or agentic systems to developer productivity, advertiser troubleshooting, or data-quality operations.

Responsibilities

Define technical strategy and investment priorities across Interfaces, Ingestion, User Match, and Conversion Quality.
Lead managers and senior technical leaders through a portfolio of multi-year ML and data-platform investments.
Partner with Product, Data Science, Ads Quality, Ads Infra, Core, Privacy, Legal, Sales, and Customer Operations.
Translate advertiser and business problems into scalable ML, data, and platform solutions.
Raise the bar for experimentation, causal measurement, model quality, reliability, privacy, and production operations.
Create mechanisms for cross-team design reviews, shared metrics, dependency management, and launch governance.
Communicate strategy, trade-offs, risks, and outcomes clearly to executives and cross-functional stakeholders.
Recruit, retain, and develop a high-performing, inclusive organization.