<p>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. We're looking for a Content Engineer to join our AI Discovery team and help define how Meta evaluates and improves AI content experiences. You'll work at the intersection of content quality, AI evaluation, and the search and recommendation systems that power Meta's products: building the frameworks, rubrics, and pipelines that hold AI outputs to a high standard. You'll assess model behavior, identify where it falls short, and work cross-functionally with engineering, product, research, and data science teams to make it better. If you're energized by the opportunity to build better AI product experiences through rigorous evaluation, have experience navigating ambiguity by defining structure, prioritizing work, and driving clarity in evolving problem spaces, and apply sound editorial and analytical judgment to content quality decisions, we encourage you to apply.</p> <p>Minimum Qualifications</p> <ul> <li>5+ years of experience working collaboratively with product, engineering, design, and user research teams </li><li>1+ years working with generative AI products, AI evaluation, prompt engineering, annotation, and/or content labeling and analysis </li><li>Experience designing and implementing evaluation frameworks, annotation guidelines, or quality rubrics for AI/ML systems </li><li>Demonstrated data analysis skills, with experience exploring data, identifying patterns, and producing actionable insights </li><li>Experience building new products or platform/ecosystem products </li><li>Critical thinking, experience leading data-driven analyses to inform product or content decisions, and experience communicating to executive leadership </li><li>Proven track record of cross-functional collaboration and delivering results in environments with evolving requirements and competing priorities </li></ul> <p>Preferred Qualifications</p> <ul> <li>Experience with Python, SQL, or other tools for data analysis and evaluation automation </li><li>Familiarity with AI evaluation methods such as human eval, model-as-judge, A/B testing, or red-teaming </li><li>Experience building dashboards, scripts, or workflows that codify evaluation metrics </li><li>Background in content strategy, information quality, or trust and safety </li><li>BA or BS in Computer Science, Data Science, Linguistics, or related field </li><li>Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements) </li><li>Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews) </li><li>Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies </li></ul> <p>Responsibilities</p> <ul> <li>Define content quality standards and use them to systematically evaluate how AI models are performing across our products and content experiences </li><li>Design golden sets, taxonomies, and guidelines that enable consistent, repeatable content quality assessments </li><li>Build repeatable workflows for collecting, annotating, and analyzing AI outputs so evaluations can run efficiently as models evolve </li><li>Evaluate successive model releases through structured comparison, documenting what improved, what regressed, and what to prioritize next </li><li>Design evaluation frameworks that integrate qualitative and quantitative signals to measure dimensions like user trust, content depth, and topical relevance </li><li>Develop processes to track content quality and model performance over time and flag regressions </li><li>Synthesize evaluation results into structured error patterns and concrete recommendations that engineering and product teams can act on </li><li>Work cross-functionally with engineers, data scientists, product managers, and content strategists to align AI behaviors with real-world user expectations </li></ul> <p>About Meta</p> <p>Meta builds technologies that help people connect, find communities, and grow businesses. When Facebook launched in 2004, it changed the way people connect. Apps like Messenger, Instagram and WhatsApp further empowered billions around the world. Now, Meta is moving beyond 2D screens toward immersive experiences like augmented and virtual reality to help build the next evolution in social technology. People who choose to build their careers by building with us at Meta help shape a future that will take us beyond what digital connection makes possible today-beyond the constraints of screens, the limits of distance, and even the rules of physics.</p> <p>Equal Employment Opportunity</p> <p>Meta is proud to be an Equal Employment Opportunity employer. We do not discriminate based upon race, religion, color, national origin, sex (including pregnancy, childbirth, reproductive health decisions, or related medical conditions), sexual orientation, gender identity, gender expression, age, status as a protected veteran, status as an individual with a disability, genetic information, political views or activity, or other applicable legally protected characteristics. You may view our Equal Employment Opportunity notice here.</p> <p>Meta is committed to providing reasonable accommodations for qualified individuals with disabilities and disabled veterans in our job application procedures. If you need assistance or an accommodation due to a disability, fill out the Accommodations request form.</p>