Staff Machine Learning Engineer, Ads Conversion Core Modeling

Overview As Staff Machine Learning Engineer, you will lead the technical vision for the Ads Conversion Core Modeling team and build state-of-the-art ML systems at scale. You will design large-scale DNN models to predict user actions with low latency and fuse text, visual, and behavioral signals to infer user interests. You’ll accelerate analysis and iteration with AI while ensuring correctness and quality, and automate routine tasks to speed development. You will mentor engineers and collaborate with product and sales to shape new ad products. This role offers meaningful impact on Pinterest’s global marketplace and AI-driven product strategy. ResponsibilitiesLead the technical direction and development of applied ML projects for ads conversionDesign and build large-scale DNN models to improve user action prediction with low latencyMine text, visual, and user signals to understand intention and infer interestsUse AI to speed up analysis and iteration with governance for correctnessAutomate repeatable tasks (documentation, reporting, QA checks)Coach and mentor engineers and collaborate with product and sales to design new ad products Key requirementsBachelor's degree in Computer Science, Statistics, or related field6+ years of industry experience building production ML systems at scale (Search, Recommendations, or Ranking)2+ years of experience leading technical projects or teamsExperience with AI coding assistants (Cursor, Copilot, Codex) for development, debugging, testing, refactoringFamiliarity with LLM-powered productivity tools for docs, search, analysis, and workflow accelerationHigh integrity and ownership; accountable for final deliverablesStrong mathematical foundation and experience with statistics and A/B testingleadership and mentoringcross-functional collaborationownership and accountabilitylarge-scale deep learning models (DNN)ML systems at scale (production)text, visual, and user signal processing