About This Role Interview language: English In this hourly, remote contractor role, you will work as an Odia (Oriya) Quality Assurance Lead (QAL) to oversee quality, consistency, and trainer performance across Odia AI training projects. You will review AI-generated Odia content and trainer/QA work, evaluate output quality against project guidelines, provide precise written feedback, and help ensure that all contributors follow the expected standards. You will assess work for accuracy, fluency, grammar, spelling, tone, cultural appropriateness, meaning preservation, instruction-following, formatting, and adherence to project-specific rubrics. You will spot recurring quality issues, communicate updates to trainers and QAs, support onboarding, maintain documentation, and help activate contributors who are not working consistently. This role requires strong Odia and English skills, excellent attention to detail, structured communication, and the ability to manage quality workflows across remote teams. This role is with SME Careers, a fast-growing AI Data Services company and subsidiary of SuperAnnotate, delivering training data for many of the world’s largest AI companies and foundation-model labs. Your Odia quality leadership will directly help improve the world’s premier AI models by ensuring that Odia training data is natural, accurate, culturally appropriate, well-documented, and aligned with client expectations. Selection process involves an AI interview, a domain-specific task, and an interview with a recruiter. Your profile Bachelor’s or Master’s degree in Odia, Linguistics, Translation, Communications, Journalism, English, Education, Quality Assurance, or a relevant domain/related field. Native or near-native Odia proficiency with strong reading and writing skills. Strong grasp of the English language to follow project guidelines, communicate with teams, and provide clear feedback in English. 3+ years of professional experience in Odia writing, editing, translation, localization, content QA, AI training, education, annotation, or related language-review workflows. Strong understanding of Odia grammar, spelling conventions, punctuation, tone, register, and cultural context. Ability to evaluate Odia content against detailed rubrics and identify issues such as mistranslation, literal phrasing, unnatural tone, hallucinated claims, ambiguity, or inconsistent terminology. Experience leading or supporting remote teams of trainers, annotators, reviewers, editors, or QAs is strongly preferred. Comfortable working in fast-moving remote environments using tools such as Discord, Google Sheets, Google Docs, trackers, dashboards, and project management systems. Highly detail-oriented and organized, with the ability to maintain style guides, FAQs, trackers, onboarding materials, honeypots, and other quality documentation. Experience with AI training, data annotation, large language models, prompt/response evaluation, or rubric-based LLM QA is a strong plus. Key responsibilities Task Description: Review and quality-check existing translations of English science benchmark questions (ARC) in your target language. For each item, you’ll compare the original translation and an AI-proposed correction against the English source, focusing strictly on accuracy and faithfulness rather than stylistic improvement . You’ll review the question and answer choices only , select the appropriate outcome (accept the original, accept the AI correction, edit the final translation, or escalate), and provide a brief review comment. The goal is to preserve the source exactly - including its meaning, difficulty, answer structure, scientific terminology, and protected elements - while following the provided core and language-specific guidelines.