[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"job-full-time-ai-generalist-trainer-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. The role is fully remote, 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 ranking outputs, writing rationales, validation, prompt evaluation, QA evaluation, and data labeling aligned to RLHF workflows and training data quality standards.","What tasks will I do?",{"A":14,"Q":15},"AI experience is helpful but not required. You must be able to follow annotation guidelines compliance, apply analytical reasoning, and maintain high-quality evaluations.","Do I need AI experience?",{"A":17,"Q":18},"Fluency in English and German is required, including strong written comprehension in both languages.","What languages are required?",{"A":20,"Q":21},"Domains vary and can include general knowledge, customer support scenarios, writing quality, instruction following, and content safety labeling-related judgments, all aimed at model performance improvement.","What domains are covered?","full-time-ai-generalist-trainer-jobs-germany",{"desc":24,"title":25,"content":26},"Rexzone is hiring Germany-based, bilingual (English\u002FGerman) AI Generalist Trainers to support RLHF and large language model evaluation by ranking model outputs, writing rationales, and enforcing annotation guidelines compliance to strengthen training data quality and drive 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 AI systems across varied domains by reviewing, ranking, and validating model-generated outputs. Your work supports RLHF pipelines and large language model evaluation, directly influencing training data quality and model performance improvement. You will follow strict annotation guidelines compliance, apply QA evaluation checks, and document clear reasoning to ensure consistent, high-quality feedback for production-grade AI workflows.",{"h2":31,"desc":32},"Responsibilities","Evaluate and rank model-generated responses in English and German using task-specific rubrics; perform RLHF-style preference ranking and prompt evaluation to identify best outputs; write concise, evidence-based rationales that explain reasoning and support model performance improvement; run QA evaluation checks for accuracy, completeness, tone, and policy adherence; validate edge cases and flag inconsistencies, ambiguity, or unsafe content for content safety labeling escalation; apply annotation guidelines compliance and maintain consistent decision-making across tasks; label and review training data to improve training data quality, including data labeling for intent, relevance, and instruction-following; collaborate asynchronously with leads to resolve guideline questions and calibrate evaluation standards; track errors, propose guideline updates, and support continuous process improvement.",{"h2":34,"desc":35},"Basic Qualifications","Based in Germany and authorized to work from Germany; fluent in both English and German (written and reading comprehension required); strong analytical skills with the ability to compare outputs and justify rankings; exceptional attention to detail and consistency in repetitive evaluation workflows; ability to follow detailed guidelines and meet quality targets for training data quality; comfortable working independently in a fully remote environment with reliable internet access.",{"h2":37,"desc":38},"Preferred Qualifications","Prior experience in AI data labeling, annotation, or QA evaluation; familiarity with LLM evaluation, RLHF concepts, and prompt evaluation methods; experience writing clear rationales and applying rubrics to diverse content types; knowledge of content safety labeling, policy compliance, and risk-based reasoning; self-driven, organized, and able to manage throughput while maintaining annotation guidelines compliance.",{"h2":40,"desc":41},"Compensation","This is a full-time remote role with hourly compensation of $35–$40 USD per hour, depending on performance and task complexity.",{"h2":43,"desc":44},"How to Apply","Apply through Rexzone and include a brief summary of your bilingual English\u002FGerman experience and any relevant evaluation, QA, or annotation work. Candidates who demonstrate strong reasoning, consistent rankings, and high training data quality during assessments will be prioritized.","AI Data Operations"]