The Global Operations Integrity Operations Team strives to create a safe atmosphere for the Meta communities by way of reliable, scalable support, education, and care for the various people around the world who use our platforms. We pride ourselves in helping prevent online and real-world harm by building fast, scalable support systems to address safety-related incidents on our products, and by influencing others to collaborate on cross-functional initiatives. As Meta continues to build AI that augments and extends human review, the role of human experts is critical to provide the oversight, governance, and authoritative judgment that keep those systems accurate, accountable, and aligned to policy. This role sits at the center of that shift. You will act as a human expert and decision-maker on the hardest and highest-stakes cases, and you will govern human review measurement as well as how AI and ML models make decisions across integrity and support use cases, setting the standards, guardrails, and human-in-the-loop checks that determine when a model can act on its own and when a human must weigh in. You will own the expert-labelled data and adjudication that trains, evaluates, and calibrates these models, ensuring their accuracy and relevance across both integrity and support. Those who join our teams are passionate about solving people's issues, are advocates for the Facebook and Instagram communities, and are energized by shaping how AI is trusted to act on their behalf.
Responsibilities
Serve as a human expert and provide well-reasoned recommendations on ambiguous, high-severity, and precedent-setting cases, and adjudicate escalations involving potentially abusive content or real-world threats
• Support AI oversight and governance for integrity and support decisioning: define how AI and ML models are reviewed, audited, and held accountable, and set the human-in-the-loop and human-out-of-the-loop thresholds that govern when models can act autonomously
• Establish and steward expert-labelled ("golden") datasets used to train, evaluate, and calibrate AI/ML models, owning label quality, precision/recall, model-agreement measurement, and drift over time
• Apply and uphold governance frameworks (quality standards, guardrails, and escalation paths) that ensure model decisions and data labels comply with all policy, regulatory, and legal requirements
• Analyze and audit model and operational data to identify user trends, malicious actor behavior, systematic model errors, and coverage gaps, and translate findings into recommendations that improve enforcement accuracy at scale
• Partner with Engineering, Data Science, and Product to improve labelling interfaces, oversight tooling, and the mechanisms by which human judgment feeds back into model performance
• Become a recognized expert in integrity and support issues across Operations at Meta and how they affect our community
• Build cross-functional partnerships to create better, more trustworthy AI-driven solutions for our community and users
Minimum Qualifications
• Currently has, or is in the process of obtaining a Bachelor's degree in a directly related field, or equivalent practical experience. Degree must be completed prior to joining Meta
• Bachelor's degree (BA/BS)
• 3+ years of experience in an operations, technology, management consulting, or equivalent environment
• 3+ years of experience in a role involving strategic/analytical initiatives (project management, consulting, data analysis, or technical systems) and/or customer operations
• Experience owning quality, decision-making, or oversight processes, setting standards and exercising authoritative judgment on complex cases
• Experience communicating with a variety of audiences, including engineering, data science, and technical teams
• Demonstrable experience using sound judgment and exhibiting maintaining clear, structured decision-making when handling time-sensitive or high-severity cases
Preferred Qualifications
• Experience identifying systemic issues through data analysis and translating findings into actionable process or policy improvements
• Knowledge of programming languages such as Python, R, or SQL
• Experience with AI/ML oversight, human-in-the-loop workflows, model evaluation, or annotation/labelling quality
• Avid user of our platform of products
• 2+ years of experience working with data tools such as SQL, SAS, and data visualization (e.g. Tableau) tools
• Familiarity with AI governance, trust & safety, or content/integrity policy
