[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"job-ai-generalist-trainer-hiring-may-2026-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 ranking model responses, writing rationales, completing prompt evaluation, running QA evaluation, and performing validation to improve training data quality and model performance improvement.","What tasks will I do?",{"A":14,"Q":15},"AI experience is helpful but not always required. Strong analytical skills, attention to detail, and consistent annotation guidelines compliance are essential; we provide task-specific guidance.","Do I need AI experience?",{"A":17,"Q":18},"Fluency in both English and German is required, including professional-level reading and writing.","What languages are required?",{"A":20,"Q":21},"Domains vary by project and may include general knowledge, instruction following, reasoning, content safety labeling, and other areas relevant to RLHF and training data quality.","What domains are covered?","ai-generalist-trainer-hiring-may-2026-germany",{"desc":24,"title":25,"content":26},"Rexzone is hiring Germany-based, bilingual (English\u002FGerman) AI Generalist Trainers to support large language model evaluation through RLHF-style ranking, prompt evaluation, and QA evaluation—improving training data quality, annotation guidelines compliance, and 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\u002FLLM workflows by reviewing model-generated outputs, ranking responses, and writing clear rationales. Your work directly supports RLHF, training data quality, and large language model evaluation to drive measurable model performance improvement. You will follow annotation guidelines compliance requirements, complete prompt evaluation and QA evaluation tasks, and contribute to content safety labeling where needed. This is a full-time, remote role for candidates located in Germany with fluent English and German.",{"h2":31,"desc":32},"Key Responsibilities","Perform large language model evaluation by assessing and ranking model outputs against rubrics; execute RLHF-style preference ranking and pairwise comparisons with well-structured reasoning; conduct QA evaluation, validation checks, and audits to ensure training data quality; write concise, evidence-based rationales in English and German that justify rankings and corrections; apply annotation guidelines compliance consistently across tasks, including prompt evaluation and data labeling; flag policy issues and complete content safety labeling when required; track edge cases, document uncertainties, and provide feedback to improve guidelines and model performance improvement; collaborate asynchronously with operations and quality teams to resolve disagreements and maintain high inter-annotator consistency.",{"h2":34,"desc":35},"Basic Qualifications","Must be based in Germany and able to work remotely from Germany; fluent in English and German (professional reading and writing required); strong analytical skills with the ability to compare outputs, detect subtle errors, and explain reasoning; exceptional attention to detail and consistency when following rubrics and annotation guidelines compliance; comfort working with ambiguity, making defensible judgments, and performing validation and QA evaluation tasks; reliable internet connection and ability to meet productivity and quality targets.",{"h2":37,"desc":38},"Preferred Qualifications","Prior experience in AI data labeling, LLM evaluation, RLHF, prompt evaluation, or content review; familiarity with large language model evaluation concepts (hallucinations, factuality, instruction-following, safety); experience applying annotation guidelines and producing high-quality rationales at scale; self-driven, organized, and comfortable working independently in a remote environment; interest in improving training data quality and contributing to ongoing model performance improvement.",{"h2":40,"desc":41},"Compensation","Pay is $35–$40 USD per hour (based on skills, quality, and task complexity).",{"h2":43,"desc":44},"How to Apply","Apply to Rexzone with a brief summary of your Germany-based remote setup, English\u002FGerman proficiency, and any experience with LLM evaluation, RLHF, data labeling, or QA evaluation. Selected candidates will complete an assessment focused on ranking, reasoning, and annotation guidelines compliance.","AI Data Operations"]