[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"job-ai-generalist-trainer-jobs-leipzig-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 remote, full-time role, and you must be based in Germany.","Is this role remote?",{"A":11,"Q":12},"You will evaluate and rank model-generated outputs, perform QA evaluation, write rationales that explain your reasoning, validate work against annotation guidelines compliance, and support large language model evaluation and training data quality improvements.","What tasks will I do?",{"A":14,"Q":15},"AI experience is helpful but not always required. Strong analytical skills, attention to detail, and the ability to follow annotation guidelines and provide clear reasoning are essential.","Do I need AI experience?",{"A":17,"Q":18},"Fluency in both English and German is required, including reading and writing for evaluation and rationale tasks.","What languages are required?",{"A":20,"Q":21},"You may work across general knowledge, customer-style prompts, writing and summarization, reasoning tasks, and content safety labeling, depending on project needs.","What domains are covered?","ai-generalist-trainer-jobs-leipzig-germany",{"desc":24,"title":25,"content":26},"Rexzone is hiring Germany-based AI Generalist Trainers to support AI\u002FLLM workflows through RLHF-style evaluation, prompt evaluation, and large language model evaluation. You will assess, rank, and QA model outputs in English and German, write clear rationales, and follow annotation guidelines compliance to strengthen training data quality and drive model performance improvement. This is a remote, full-time role focused on training data quality, safety-aware labeling, and reliable evaluation for production AI systems.","Germany-Based English & German AI Generalist Trainer 2026 May",[27,30,33,36,39],{"h2":28,"desc":29},"About the Role","As an AI Generalist Trainer at Rexzone, you will evaluate and improve model behavior by reviewing model-generated responses, comparing alternatives, and providing reasoning-rich feedback. Your work directly supports RLHF pipelines, training data quality, and model performance improvement. You will apply annotation guidelines compliance, perform QA evaluation, and contribute to large language model evaluation across a variety of user scenarios in both English and German.",{"h2":31,"desc":32},"Key Responsibilities","Evaluation, ranking, and QA of model-generated outputs in English and German; write concise rationales explaining preferences and reasoning; validate task outputs against annotation guidelines compliance and project policies; perform prompt evaluation and consistency checks to improve training data quality; identify defects, safety issues, and edge cases using content safety labeling; collaborate with leads to calibrate scoring rubrics and improve labeling accuracy; document decisions and support ongoing model performance improvement through structured feedback.",{"h2":34,"desc":35},"Basic Qualifications","Based in Germany and eligible to work remotely from Germany; fluent in English and German (reading, writing, and comprehension); strong analytical skills and comfort comparing nuanced answers; excellent attention to detail with consistent annotation guidelines compliance; ability to explain reasoning clearly and follow evaluation rubrics; reliable time management for full-time delivery and QA evaluation.",{"h2":37,"desc":38},"Preferred Qualifications","Prior experience with data labeling, LLM evaluation, QA evaluation, or RLHF-related workflows; familiarity with large language model evaluation and prompt evaluation; experience writing high-quality rationales and performing validation; self-driven, quality-focused, and comfortable working independently in a remote environment.",{"h2":40,"desc":41},"How to Apply","Apply to Rexzone with a brief summary of your bilingual English\u002FGerman experience and any relevant evaluation, annotation, or QA work. Candidates who demonstrate strong reasoning, careful validation, and consistent training data quality standards will be prioritized.","AI Data Operations"]