German QA Lead - Remote

The position of German Quality Assurance Lead is a remote, hourly contract role with a fast‑growing AI data‑services firm that supplies training material to many of the world’s leading artificial‑intelligence developers. In this capacity you will steer the quality, uniformity and performance of trainers working on German‑language AI projects, ensuring that the data fed to models is natural, precise and culturally appropriate. Your everyday tasks will involve examining AI‑produced German text and the work of trainers, measuring each piece against detailed project rubrics, and delivering clear written comments. You will monitor for errors in accuracy, fluency, grammar, spelling, tone, cultural relevance, meaning preservation and formatting, while flagging systematic problems. Communication will flow through Discord and other collaboration tools, where you will inform trainers of guideline changes, answer language‑related queries, reactivate contributors who have lapsed, and keep style guides, FAQs, trackers and onboarding resources up to date. You will also lead training calls to convey expectations and help refine quality‑control processes. Candidates must hold a bachelor’s or master’s degree in German, linguistics, translation, communications, journalism, English, education, quality assurance or a comparable discipline, and possess native‑level German reading and writing abilities. Strong command of English is required for interpreting guidelines and drafting feedback. At least three years of professional experience in German writing, editing, translation, localization, content QA, AI training, education or annotation is essential, together with deep familiarity with German grammar, punctuation, case usage, compound formation, tone, register and regional variations across Germany, Austria and Switzerland. Experience supervising remote language teams and comfort with platforms such as Discord, Google Sheets, Docs and project‑management dashboards are also expected. Additional assets include prior involvement with AI‑training pipelines, data annotation, large‑language‑model evaluation or rubric‑based quality assessment. The role offers entry into an expert network that will be contacted for upcoming assignments