Lead, Product Content Engineering at Meta in New York City, NY

{"title": "Lead, Product Content Engineering", "description": "{\"__html\":\"\\u003Cspan>Product Content Engineering is a horizontal function supporting initiatives across Meta's family of apps. We partner closely with product and technical teams to solve problems by providing content-centered solutions, setting standards of quality, and building the frameworks that ensure AI-powered experiences actually work for people.\\n\\nWe're looking for an experienced manager to join our team and help define how Meta evaluates and improves AI content experiences and manage a team of team members across a variety of projects. You will take on the highest priority work and flex as we continue to transform the team and uplevel the AI capabilities at all levels. The work is time-sensitive and innovative, situated at the intersection of content expertise and Meta's industry-leading ranking and delivery systems.\\n\\nThe manager in this role will apply technical expertise to drive change in evolving environments with shifting priorities. You will be expected to perform data analysis, comprehend complex recommendation systems, and test hypotheses while driving alignment across a wide cross-functional team to deliver business impact at scale.\\u003C\\/span>\"}", "minimum_qualifications": ["10+ years of experience improving content quality and relevance on content platforms, including work with video creators, ranking systems, content strategy", "3+ years of professional experience in hiring, managing and developing individual contributors", "1+ year working with GenAI products, prompt engineering, annotation, and/or content evaluation and analysis", "Experience driving cross-functional projects autonomously to build products, respond to urgent needs, preempt issues and address concerns in a collaborative and timely fashion", "Familiarity with AI industry trends demonstrated through past work applying them to content strategy and the ability to translate them into actionable content strategy", "Experience applying critical thinking to lead data-driven analyses that inform product or content decisions, and communicating findings to executive leadership"], "preferred_qualifications": ["Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews)", "2+ years of experience working closely with ranking teams", "BA or BS in Computer Science, Data Science, Linguistics, or related field", "Experience with data visualization tools such as Tableau", "Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies", "Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements)", "4+ years of work experience in product management, data analytics, or content operations in a large-scale content platform"], "responsibilities": ["Develop and execute strategies for Meta's product teams to evaluate LLMs at scale across content work", "Build, lead, and mentor a team of content engineers, fostering a culture of creativity, excellence, and professional growth", "Drive sprints for LLM evaluations and automated evaluation tooling while devising and implementing systems to increase evaluation capacity", "Understand technical product needs and translate those into actionable direction for content-focused cross-functional teams", "Understand Meta's strategic and competitive position and deliver content strategies and product solutions that are aligned with our mission and aligned with our mission and competitive in the industry", "Define emergent opportunities and drive impact via execution in highly ambiguous areas", "Lead cross-functionally with engineering, data science, and product teams to align AI behaviors and content experiences with real-world user expectations"], "locations": ["Menlo Park, CA", "New York, NY", "San Francisco, CA"], "departments": ["Data & Analytics"], "public_compensation": [{"error_apology_note": "", "has_bonus": true, "has_equity": true, "compensation_amount_minimum": "$242,000/year", "compensation_amount_maximum": "$296,000/year"}]}