Overview As an engineering leader at Pinterest, you will define the technical direction for advertiser measurement and signal quality, guiding a multi-team portfolio. You will build and scale ML and data platforms, prioritize multi-year investments, and partner with product, data science, and privacy teams to translate business challenges into scalable solutions. You'll raise the bar on experimentation, model quality, and production reliability while shaping governance and cross-team collaboration. This role offers impact at scale within a mission-driven, inclusive engineering culture. You'll lead with clarity, influence across functions, and a focus on measurable outcomes that advance advertising to
Compensation / Benefits- equity offered
- base salary range disclosed
- hybrid work model ()
- salary transparency
- competitive benefits
- relocation not offered
Responsibilities- Define technical strategy and investment priorities across Interfaces, Ingestion, User Match and Conversion Quality
- Lead managers and senior engineers through a portfolio of multi-year ML and data-platform investments
- Partner closely with Product, Data Science, Ads Quality, Infra, Privacy, Legal, Sales and others to solve advertiser problems
- Translate advertiser and business challenges into scalable ML, data, and platform solutions
- Raise the bar for experimentation, causal measurement, model quality, reliability and privacy
- Create mechanisms for cross-team design reviews, shared metrics, dependency management, and launch governance
- Communicate strategy, risks and outcomes to executives and stakeholders
- Recruit, retain and develop a high-performing, inclusive organization
Key requirements- Strong background in ads measurement, identity, signals and large-scale data processing
- Experience leading an engineering organization through managers and senior technical leaders
- Proven ability to define and execute technical strategy across multiple teams
- Experience operating systems with scale, reliability, privacy and data-quality requirements
- Track record of improving organizational execution and developing leaders
- Exceptional analytical thinking and ability to translate ambiguous problems into measurable outcomes
- Strong executive communication and cross-functional influence
- Bachelor's degree in computer science, statistics, machine learning, or equivalent experience
- Executive communication
- Cross-functional influence
- Leadership and people development
- Ads measurement, identity, signals, large-scale data processing
- ML platforms, real-time or streaming systems
- Privacy, data-quality, and governance
