[Remote] Sr. Staff Machine Learning Engineer, Content Ecosystem

Note: The job is a remote job and is open to candidates in USA. Pinterest is a platform dedicated to providing creative inspiration to users worldwide. They are seeking a Sr. Staff Machine Learning Engineer to lead the technical strategy for improving the content ecosystem, focusing on the health and performance of content through machine learning and optimization.ResponsibilitiesSet technical strategy and vision for ML systems that improve the end-to-end content ecosystem, including supply, distribution, and engagement/utility outcomesPartner with DS teams to develop a content ecosystem measurement framework to quantify content health and performance (e.g., content quality, freshness, diversity, coverage, creator/content sustainability, and user value), and align it with company/business goalsIdentify and close content gaps by building models and insights that answer: what content is missing, for whom, in which contexts, and whyDeeply understand what content works and why by combining causal thinking, experimentation, and model interpretability to connect content attributes and distribution mechanisms to downstream user and business outcomesBuild and optimize content marketplace mechanisms that balance multi-sided incentives and constraints (e.g., users, creators/publishers, advertisers, internal policy/safety), while maximizing long-term ecosystem valueDesign multi-objective optimization approaches that manage tradeoffs across relevance, quality, diversity, creator incentives, integrity/safety, and monetizationPartner closely with cross-functional teams (Product, Data Science, UX Research, Content/Creator teams, Trust & Safety, Ads, Infra) to translate ambiguous ecosystem problems into clear technical roadmaps and deliver measurable impactMentor and grow junior ML engineers through technical coaching, design reviews, career development support, and creating a culture of strong engineering and scientific rigorRaise the quality bar for ML engineering by establishing best practices for data quality, model governance, reliability, privacy-aware design, and operational excellenceCommunicate clearly and influence broadly by producing crisp technical proposals, aligning stakeholders on tradeoffs, and driving decisions across org boundariesExplore and apply advanced methods where beneficial—e.g., game-theoretic approaches, reinforcement learning, mechanism design, or bandit-style optimization—to improve marketplace dynamics and long-term ecosystem outcomesSkillsStrong fundamentals in machine learning and optimization, with the ability to apply them to real-world, high-scale ecosystem problemsDemonstrated ability to lead technical strategy, navigate ambiguity, and deliver end-to-end impactDeep interest in marketplace dynamics (multi-sided incentives, feedback loops, long-term health metrics), and comfort with multi-objective tradeoffsExperience with Cursor, Copilot, Codex, or similar AI coding assistants for development, debugging, testing, and refactoringFamiliarity with LLM-powered productivity tools for documentation search, experiment analysis, SQL/data exploration, and engineering workflow accelerationDegree in Computer Science, Engineering, a related field or equivalent experienceBackground in game theory, reinforcement learning, mechanism design, or causal inference applied to ecosystems/marketplacesBenefitsThe position is also eligible for equity.Information regarding the culture at Pinterest and benefits available for this position can be found here.Relocation Statement : This position is not eligible for relocation assistance.In-Office Requirement Statement : This role will need to be in the office for in-person collaboration 1-2 times every 6 months and therefore can be situated anywhere in the country.Company OverviewPinterest is a visual bookmarking tool for saving and discovering creative ideas. It was founded in 2010, and is headquartered in San Francisco, California, USA, with a workforce of 1001-5000 employees. Its website is https://www.pinterest.com/.