[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"job-entry-level-german-speaking-ai-generalist-trainer-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, and 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, ranking, QA evaluation, validation, prompt evaluation, and writing reasoning-based rationales to improve training data quality and model performance improvement.","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 the ability to follow annotation guidelines compliance; training is provided for task standards.","Do I need AI experience?",{"A":17,"Q":18},"Fluency in both English and German (written and reading comprehension) is required for bilingual evaluation and labeling.","What languages are required?",{"A":20,"Q":21},"You may evaluate across multiple domains, including general knowledge, reasoning, summarization, instruction following, and content safety labeling, depending on project needs.","What domains are covered?","entry-level-german-speaking-ai-generalist-trainer-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 reviewing, ranking, and QA-checking model outputs. You will apply annotation guidelines compliance to improve training data quality, write clear rationales, and drive model performance improvement through consistent evaluation and validation of responses across domains.","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 model-generated outputs in AI\u002FLLM workflows, perform RLHF-style ranking and prompt evaluation, and validate results against annotation guidelines. Your work directly improves training data quality and supports model performance improvement by producing high-quality labels, QA evaluation, and reasoning-based rationales for large language model evaluation.",{"h2":31,"desc":32},"Key Responsibilities","Evaluate and rank model responses in English and German for large language model evaluation; perform QA evaluation and validation checks to ensure training data quality; write structured reasoning rationales that justify rankings and identify errors; label and annotate data following annotation guidelines compliance, including prompt evaluation and content safety labeling when required; audit edge cases, escalate policy ambiguities, and propose updates to annotation guidelines; track disagreement patterns, calibrate decisions with team standards, and improve consistency across evaluators; support dataset sampling, error analysis, and iterative model performance improvement through feedback loops.",{"h2":34,"desc":35},"Basic Qualifications","Must be based in Germany and eligible to work as a remote contractor\u002Fworker as applicable; fluent in English and German (reading and writing); strong analytical skills with the ability to compare outputs, detect subtle issues, and apply consistent evaluation criteria; high attention to detail and comfort following annotation guidelines compliance; ability to write concise, well-structured rationales explaining evaluation, ranking, and validation decisions; reliable internet connection and ability to work full-time on a remote schedule.",{"h2":37,"desc":38},"Preferred Qualifications","Prior experience with data labeling, QA evaluation, or content review; familiarity with RLHF, LLM evaluation, and prompt evaluation concepts; experience applying annotation guidelines and maintaining training data quality in production workflows; self-driven and comfortable managing workload independently while meeting quality targets; interest in cross-domain evaluation (e.g., general knowledge, reasoning, summarization, safety) to support model performance improvement.",{"h2":40,"desc":41},"Compensation","Pay: $35–$40 USD per hour, depending on performance, task complexity, and quality outcomes. This role is remote and full-time.",{"h2":43,"desc":44},"How to Apply","Apply through Rexzone with your up-to-date resume\u002FCV and a brief note highlighting bilingual English\u002FGerman proficiency and any experience in evaluation, QA, data labeling, or annotation guidelines.","AI Data Operations"]