{"html":"<p>In this hourly, remote contractor role, you will work as a Japanese Quality Assurance Lead (QAL) to oversee quality, consistency, and trainer performance across Japanese AI training projects. You will review AI-generated Japanese content and trainer/QA work, evaluate output quality against project guidelines, provide precise written feedback, and ensure that all contributors follow the expected quality standards.</p>\n<p>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.</p>\n<p>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 Japanese quality leadership will directly help improve the world’s premier AI models by ensuring that Japanese training data is natural, accurate, culturally appropriate, well-documented, and aligned with client expectations.</p>\n<p>Selection process involves an AI interview, a domain-specific task, and an interview with a recruiter.</p>\n<p>Important:\nThere is no immediate project for this role; however, if qualified, you will be among the first experts we reach out to when relevant opportunities arise. This will also provide you with access to future projects available through our expert network.</p>\n<h3>Responsibilities</h3><ul><li>Spot-check Japanese items, identify quality issues, provide feedback through DMs, and escalate recurring or critical issues.</li><li>Update trainers and QAs on Discord about guidelines, project changes, workflow updates, and quality expectations.</li><li>Respond to questions around Japanese grammar, keigo, register, kana/kanji usage, translation fidelity, cultural context, terminology, and edge cases.</li><li>DM inactive contributors, encourage activation, track follow-ups, and flag availability issues.</li><li>Create and maintain Japanese documentation, style guides, trackers, FAQs, quality notes, examples, honeypots, and onboarding materials.</li><li>Run onboarding/training calls to explain workflows, rubrics, quality standards, and Japanese-specific requirements.</li><li>Ensure all trainers and QAs apply Japanese language guidelines consistently.</li><li>Identify recurring quality gaps and build scalable QA processes.</li></ul><h3>Requirements</h3><ul><li>Bachelor’s or Master’s degree in Japanese, Linguistics, Translation, Communications, Journalism, English, Education, Quality Assurance, or a relevant domain/related field.</li><li>Native or near-native Japanese proficiency, with strong reading and writing skills.</li><li>Strong grasp of the English language to follow project guidelines, communicate with teams, and provide clear feedback in English.</li><li>3+ years of professional experience in Japanese writing, editing, translation, localization, content QA, AI training, education, annotation, or related language-review workflows.</li><li>Strong understanding of Japanese grammar, kana/kanji usage, punctuation, keigo, tone, register, honorifics, cultural context, and Japan-specific localization.</li><li>Ability to evaluate Japanese content against detailed rubrics and identify issues such as mistranslation, literal phrasing, unnatural tone, incorrect keigo, ambiguous references, hallucinated claims, or inconsistent terminology.</li><li>Experience leading or supporting remote teams of trainers, annotators, reviewers, editors, or QAs is strongly preferred.</li><li>Comfortable with Discord, Google Sheets, Google Docs, trackers, dashboards, and project management systems.</li><li>Highly detail-oriented and organized, with the ability to maintain style guides, FAQs, trackers, onboarding materials, honeypots, and documentation.</li><li>Experience with AI training, data annotation, LLM evaluation, prompt/response evaluation, or rubric-based LLM QA is a strong plus.</li></ul>"}