Evaluator/Reviewer - English Language & Literature Teachers, Postsecondary

About this role

Role Overview The Occupation-Specific Reviewer evaluates task submissions that require domain expertise in a specific profession or field (e.g., healthcare, law, education, engineering, finance, software development). This role ensures that content is not only guideline-compliant, but also professionally accurate, realistic, and aligned with real-world standards of practice. Occupation-Specific Reviewers are trusted subject matter experts who apply both formal evaluation criteria and professional judgment, while maintaining strict adherence to safety, compliance, and scope boundaries. Key Responsibilities - Review submissions requiring professional or technical domain knowledge - Validate factual accuracy, terminology, and real-world applicability within the domain - Ensure outputs remain within allowed scope and do not provide unsafe, misleading, or non-compliant guidance - Evaluate alignment with professional standards, norms, and best practices - Apply platform guidelines consistently, even when they conflict with personal preference or real-world shortcuts - Provide precise, educational, and corrective feedback grounded in both guidelines and domain expertise - Identify high-risk errors related to safety, ethics, or misuse - Escalate ambiguous or high-impact issues appropriately - Maintain clear documentation of review decisions and reasoning Required Qualifications - Advanced degree, professional certification, or equivalent experience in the relevant occupation or field - 5+ years of professional experience practicing in that domain - Demonstrated experience with: -- Evaluation, review, auditing, or supervisory responsibilities OR -- Teaching, mentoring, training, or assessing professional work - Strong understanding of professional boundaries, risk, and compliance considerations - Excellent written communication skills suitable for formal feedback Preferred Qualifications - Prior experience reviewing AI-generated or training data content - Familiarity with