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The Machine Learning Engineer will develop and improve ML models for product surfaces, build data processing pipelines, and leverage machine learning technologies in advertisements.

Leads Pinterest’s programmatic advertising sales strategy, team, and revenue growth. Builds executive and partner relationships, develops go-to-market plans, drives adoption of programmatic and AdTech solutions, and represents Pinterest at industry events. Collaborates with Product, Engineering, Measurement, Agencies, and other teams to shape scalable offerings and product roadmaps. Tracks performance, develops sales playbooks, and delivers client solutions using expertise in DSPs, SSPs, auction mechanics, deal structures, measurement, Clean Rooms, and AI-powered advertising.

Design, build, and operate full‑stack and backend services to support Sales, Marketing, and Finance. Lead technical design and production deployment of GenAI/ML features, own SDLC, ensure observability and validation, partner with cross-functional teams, and mentor engineers to deliver business outcomes.

The role involves building ML systems, improving models across product surfaces, and leveraging data for personalization and user engagement.

As a Senior Data Scientist in Monetization, you'll lead data product development, conduct strategic analysis, build models, track success metrics, and mentor junior data scientists.

Develop and improve machine learning models for Pinterest's various product surfaces, utilizing deep learning and advanced data processing.

Develop and execute ML technology stack vision for Ads, improve ML models, and enhance content understanding using LLMs in a collaborative environment.

Drive data-science for people- and business-facing products: establish experimentation and instrumentation best practices, apply statistical and ML methods to web-scale data, build scalable analysis pipelines, and partner cross-functionally to turn insights into product improvements.

Technical lead for forecasting: design and deploy production time‑series models at scale, own end‑to‑end modeling lifecycle, set technical vision for forecasting platform, translate forecasts into executive decisions, expand time‑series capabilities (anomaly detection, RCA, attribution), embed forecasts into business processes, and mentor at least two data scientists.

Drive the Compliance product roadmap for copyright, trademark, and legal reporting tools. Partner with Legal, Engineering, Operations, and other product teams to build scalable systems and workflows that ensure compliance with global and domestic content/IP legislation. Lead cross-functional projects and improve tools for rights holders to manage content at scale.