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Sr. Manager, Machine Learning Engineering, Ads Measurement Products

Pinterest · San Francisco, CA, US; Remote, US

remotesenior$227,871–$227,871Posted Sep 30, 2026machine learningcausal inferenceexperimentationprobabilistic modelinganomaly detectionmarketing mix modelingmulti-touch attributionLLMs

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About this role

**Sr. Manager, Machine Learning Engineering, Ads Measurement Products** **About Pinterest** Millions of people use Pinterest to find creative ideas, dream about new possibilities, and plan memories that last a lifetime. At Pinterest, AI is a powerful partner that augments creativity and amplifies impact. **Team Overview (Measurement Products)** The Measurement Products team helps advertisers understand campaign effectiveness, quantify business impact, and make informed investment decisions. You’ll work on first- and third-party measurement solutions (e.g., incrementality, experimentation, brand outcomes) and the scalable platforms that power them—delivering rigorous, privacy-conscious, actionable measurement. --- ## What you’ll do - Lead and grow a team of ML, backend, and data engineers building ads measurement products and platforms (incrementality solutions, measurement diagnostics, anomaly detection, automated insights, and decision-support tools). - Set the technical vision and multi-year engineering strategy for Measurement Products, translating advertiser needs and measurement methodologies into scalable, reliable, trustworthy production systems. - Partner with Product, Data Science, Ads Engineering, and Infrastructure to productionize causal inference, experimentation, and ad-effectiveness solutions without compromising methodological rigor. - Drive scalable ML and data platforms for first- and third-party measurement, including conversion lift, brand lift, budget-split testing, matched-market testing, MMM, MTA, conversion APIs, and clean-room-based measurement. - Influence the broader Ads Product and Engineering roadmap by identifying high-leverage opportunities to improve speed, scale, usability, and actionability. - Partner across Product Management, Data Science, Sales, and other functions to expand adoption and business impact. - 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 AI-assisted development and LLM-powered tools to accelerate engineering and analysis—while maintaining rigorous standards for validation, explainability, data protection, and accountability. ## What we are looking for - 10+ years building software, ML, or large-scale data systems; 5+ years managing engineering teams responsible for production systems. - Bachelor’s degree in computer science (or related field) or equivalent experience. - Meaningful experience in ads measurement / ad effectiveness / incrementality (e.g., conversion lift, brand lift, budget-split testing, matched-market testing, MMM, MTA, conversion APIs, clean-room-based measurement). - Strong understanding of experimentation, causal inference, probabilistic modeling, and measurement with noisy/incomplete/privacy-constrained data. - Proven ability to set technical vision, develop multi-year roadmaps, and deliver production-quality systems from strategy through execution. - Demonstrated success partnering across Engineering, Product Management, Data Science, Infrastructure, and business teams. - Ability to make principled trade-offs across methodological rigor, usability, system complexity, statistical power, data quality, privacy, and time to market. - Experience establishing strong engineering practices (architecture, operational excellence, experimentation, evaluation, monitoring, governance). - Track record hiring, m

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