Sr. Manager, Machine Learning Engineering, Ads Measurement Products

The Measurement Products team helps advertisers understand campaign effectiveness, quantify business impact, and make informed investment decisions. We build a portfolio of first- and third-party measurement solutions spanning incrementally, experimentation, brand outcomes, and other approaches to evaluating advertising performance.

We also develop the scalable platforms and capabilities that power these solutions, enabling faster innovation, support for evolving measurement methodologies, and integration with Pinterest’s broader ads, data, and experimentation ecosystems. Our mission is to deliver rigorous, privacy-conscious, and actionable measurement that strengthens advertiser confidence and improves business outcomes.

What you’ll do:

• Lead and grow a team of experienced ML, backend, and data engineers responsible for building innovative ads measurement products and platforms, including incrementality solutions, measurement diagnostics, anomaly detection, automated insights, and advertiser decision-support tools.
• Set the technical vision and multi-year engineering strategy for Measurement Products, translating advertiser needs and measurement methodologies into scalable, reliable, and trustworthy production systems.
• Partner closely with Product, Data Science, Ads Engineering, and Infrastructure teams to develop and productionize causal inference, experimentation, and ad-effectiveness solutions without compromising methodological rigor.
• Drive the development of scalable ML and data platforms supporting first- and third-party measurement products, including conversion lift, brand lift, budget-split testing, matched-market testing, marketing mix modeling, multi-touch attribution, conversion APIs, and clean-room-based measurement.
• Influence the broader Ads Product and Engineering roadmap by identifying high-leverage opportunities to improve the speed, scale, usability, and actionability of Pinterest’s measurement offerings.
• Partner with stakeholders across Product Management, Data Science, Sales, and other functions to expand the adoption and business impact of Pinterest’s measurement products.
• Hire, mentor, and grow engineering managers, technical leaders, and engineers. Build an inclusive culture of technical excellence, accountability, innovation, and strong cross-functional collaboration.
• Champion the effective use of AI-assisted development and LLM-powered tools to accelerate engineering, prototyping, experimentation, and analysis while maintaining rigorous standards for validation, explainability, data protection, and accountability.

What we are looking for:

• 10+ years of industry experience building software, ML, or large-scale data systems, with 5+ years of experience managing engineering teams responsible for production systems.
• Bachelor’s degree in computer science, a related field or equivalent experience.
• Meaningful experience with ads measurement, ad effectiveness, or incrementally, including areas such as conversion lift, brand lift, budget-split testing, matched-market testing, MMM, MTA, conversion APIs, or clean-room-based measurement.
• Strong understanding of experimentation, causal inference, probabilistic modeling, or measurement using noisy, incomplete, or privacy-constrained data.
• Demonstrated ability to set a compelling technical vision, develop multi-year roadmaps, and drive scalable, production-quality systems from strategy through execution.
• Proven success partnering across Engineering, Product Management, Data Science, Infrastructure, and business teams to deliver measurable product and advertiser impact.
• Ability to make principled decisions and guide teams through trade-offs involving methodological rigor, product usability, system complexity, statistical power, data quality, privacy, and time to market.
• Experience establishing strong engineering practices for architecture, operational excellence, experimentation, evaluation, monitoring, and governance.
• Track record of hiring, mentoring, and developing engineering managers, senior technical leaders, and high-performing engineers.
• Strong communication and stakeholder-management skills, with the ability to influence senior leaders and align teams across organizational boundaries.
• Experience using AI coding assistants and LLM-powered productivity tools to improve engineering and analytical workflows, paired with clear standards for critical review, testing, and accountability.

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 1-2 times per month and therefore needs to be in a commutable distance from one of the following offices: San Francisco, Palo Alto, Seattle.

Relocation Statement:

• This position is not eligible for relocation assistance. Visit our PinFlex page to learn more about our working model.

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