[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"job-no-experience-ai-annotation-jobs-germany":3},{"Ques":4,"Slug":22,"Header":23,"job_category":45},{"title":5,"content":6},"Frequently Asked Questions",[7,10,13,16,19],{"A":8,"Q":9},"Yes. This is a remote, full-time role, but you must be based in Germany.","Is this role remote?",{"A":11,"Q":12},"You will perform large language model evaluation tasks such as evaluation and ranking for RLHF, prompt evaluation, QA evaluation, validation checks, and writing clear rationales to improve training data quality.","What tasks will I do?",{"A":14,"Q":15},"AI experience is helpful but not required. We value strong analytical skills, attention to detail, and consistent annotation guidelines compliance; we provide role-specific instructions and feedback.","Do I need AI experience?",{"A":17,"Q":18},"Fluency in both English and German is required, including the ability to read and write professionally in both languages.","What languages are required?",{"A":20,"Q":21},"You will evaluate general assistant behavior across domains such as writing quality, reasoning, factuality, instruction following, and content safety labeling, aligned to training data quality and model performance improvement goals.","What domains are covered?","no-experience-ai-annotation-jobs-germany",{"desc":24,"title":25,"content":26},"Rexzone is hiring Germany-based, bilingual (English\u002FGerman) AI Generalist Trainers to support AI\u002FLLM workflows through RLHF, large language model evaluation, and training data quality work that drives model performance improvement.","Germany-Based English & German AI Generalist Trainer 2026 May",[27,30,33,36,39,42],{"h2":28,"desc":29},"About the Role","As a Germany-based English & German AI Generalist Trainer at Rexzone, you will evaluate and improve large language model outputs within modern AI\u002FLLM workflows. Your work includes RLHF-style ranking, prompt evaluation, and QA evaluation, with clear rationales that strengthen training data quality and enable measurable model performance improvement. You will follow annotation guidelines compliance requirements while helping validate model behavior across bilingual (English\u002FGerman) scenarios and content safety labeling needs.",{"h2":31,"desc":32},"Key Responsibilities","Evaluate and compare model-generated responses in English and German using defined rubrics and annotation guidelines compliance standards. Rank outputs for RLHF and reinforcement-style preference data, documenting reasoning and trade-offs. Perform QA evaluation on labeled datasets to validate consistency, correctness, and policy alignment. Write concise rationales that support large language model evaluation and downstream training data quality. Validate edge cases, ambiguous prompts, and multi-turn conversations through structured reasoning. Apply content safety labeling and policy checks, escalating uncertain cases with evidence. Track errors, perform spot checks, and propose rubric clarifications to improve annotation guidelines. Collaborate asynchronously with reviewers to resolve disagreements and maintain labeling throughput and quality targets.",{"h2":34,"desc":35},"Basic Qualifications","Must be based in Germany and able to work remotely from Germany. Fluency in both English and German (C1\u002FC2 level or equivalent) with strong writing skills in both languages. Strong analytical skills and comfort making fine-grained judgments across quality, factuality, relevance, and safety. High attention to detail and ability to follow detailed instructions and annotation guidelines compliance requirements. Ability to explain decisions clearly by writing structured rationales and validations. Reliable internet connection and ability to meet quality and productivity expectations in a remote environment.",{"h2":37,"desc":38},"Preferred Qualifications","Prior experience with data labeling, prompt evaluation, QA evaluation, or content moderation\u002Fcontent safety labeling. Familiarity with LLM evaluation, RLHF concepts, and common failure modes (hallucinations, instruction-following gaps, bias). Experience working with annotation tools and maintaining training data quality at scale. Self-driven and comfortable working independently with minimal supervision while meeting deadlines. Interest in improving model performance improvement through rigorous evaluation and feedback loops.",{"h2":40,"desc":41},"Compensation","Pay is $35–$40 USD per hour, based on skills, evaluation performance, and role fit. This is a full-time, remote role based in Germany.",{"h2":43,"desc":44},"How to Apply","Apply through Rexzone with your resume\u002FCV and a short note describing your bilingual English\u002FGerman experience and any relevant AI evaluation, data labeling, or QA evaluation background. Selected candidates may complete a brief large language model evaluation exercise focused on ranking, reasoning, and training data quality.","AI Data Operations"]