[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"job-ai-trainer-jobs-stuttgart-germany":3},{"Ques":4,"Slug":22,"Header":23,"job_category":42},{"title":5,"content":6},"Frequently Asked Questions",[7,10,13,16,19],{"A":8,"Q":9},"Yes. This is a fully remote, full-time role for candidates based in Germany.","Is this role remote?",{"A":11,"Q":12},"You will perform large language model evaluation tasks such as evaluating and ranking model outputs, completing QA evaluation, writing rationales that explain reasoning, and validating labels to improve training data quality within RLHF workflows.","What tasks will I do?",{"A":14,"Q":15},"AI\u002Fannotation experience is helpful but not required. You must be able to follow guidelines precisely, apply consistent judgment, and demonstrate strong analytical skills and attention to detail.","Do I need AI experience?",{"A":17,"Q":18},"Fluency in both German and English is required, including reading and writing with high accuracy and nuance.","What languages are required?",{"A":20,"Q":21},"Domains vary and can include general knowledge, writing quality, reasoning, instruction-following, prompt evaluation, content safety labeling, and other areas relevant to model performance improvement and training data quality.","What domains are covered?","ai-trainer-jobs-stuttgart-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 clear rationales, and enforcing annotation guidelines compliance. You will work across AI\u002FLLM workflows to strengthen training data quality and drive model performance improvement through careful evaluation, QA checks, and validation of reasoning and safety signals.","Germany-Based English & German AI Generalist Trainer 2026 May",[27,30,33,36,39],{"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 by assessing, ranking, and QA-reviewing model-generated outputs. Your work directly impacts RLHF pipelines, large language model evaluation, and training data quality. You will apply annotation guidelines compliance, document reasoning, and validate edge cases to support model performance improvement across multilingual tasks.",{"h2":31,"desc":32},"Key Responsibilities","Perform large language model evaluation by reviewing model responses for accuracy, relevance, and policy compliance; rank and compare multiple outputs using defined rubrics; conduct QA evaluation to detect inconsistency, hallucinations, and format violations; write concise rationales explaining reasoning behind rankings and corrections; validate training examples and labels for training data quality; apply annotation guidelines compliance across English and German data; execute prompt evaluation and prompt-response audits to improve instruction following; perform content safety labeling and escalation of sensitive or unsafe content; track recurring failure patterns and propose rubric clarifications; collaborate asynchronously with reviewers to resolve disagreements and improve inter-annotator consistency.",{"h2":34,"desc":35},"Basic Qualifications","Must be based in Germany and authorized to work as an independent contractor where applicable; fluent in both German and English (reading and writing) with strong command of grammar and nuance; strong analytical skills with the ability to evaluate arguments and verify factual consistency; exceptional attention to detail and ability to follow complex annotation guidelines; comfort making structured judgments, ranking outputs, and documenting reasoning; reliable internet connection and ability to meet quality and throughput targets in a remote setting.",{"h2":37,"desc":38},"Preferred Qualifications","Prior experience in AI data labeling, RLHF, LLM evaluation, or QA evaluation; familiarity with prompt evaluation methods, rubric-based ranking, and inter-annotator agreement practices; experience with content safety labeling and policy-based decision making; self-driven, organized, and able to manage time independently in a fully remote environment; interest in model performance improvement and training data quality processes.",{"h2":40,"desc":41},"How to Apply","Apply through Rexzone and include a short summary of your bilingual English\u002FGerman experience, availability, and any background in evaluation, annotation, or QA. Selected candidates may complete an online assessment focused on ranking, reasoning, validation, and annotation guidelines compliance.","AI Data Operations"]