Germany-Based English & German AI Generalist Trainer 2026 May

Rexzone is hiring Germany-based AI Generalist Trainers to support RLHF and large language model evaluation by assessing, ranking, and QA-reviewing model outputs to strengthen training data quality and drive model performance improvement. This full-time remote role requires fluent German and English for bilingual prompt evaluation, data labeling, and consistent reasoning-based validation aligned to annotation guidelines compliance.

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About the Role

As a Germany-based English & German AI Generalist Trainer at Rexzone, you will evaluate and improve AI systems by reviewing and ranking model-generated responses, writing clear rationales, and performing QA evaluation to ensure training data quality. You will work within RLHF pipelines and large language model evaluation workflows, applying annotation guidelines compliance, content safety labeling, and structured reasoning to support model performance improvement.

Responsibilities

Evaluate model-generated outputs against task goals, safety requirements, and linguistic correctness (German/English); Rank multiple responses using quality rubrics and provide defensible reasoning-based rationales; Perform QA evaluation and validation checks to detect errors, inconsistencies, bias, or guideline violations; Apply data labeling and prompt evaluation procedures with strict annotation guidelines compliance; Identify edge cases, ambiguous prompts, and failure modes, then document findings to improve training data quality; Calibrate decisions with peers and leads to maintain consistent large language model evaluation standards; Track and report quality metrics, rework drivers, and recurring patterns impacting model performance improvement.

Basic Qualifications

Based in Germany and authorized to work remotely from Germany; Fluency in German and English (reading, writing, and comprehension) for bilingual evaluation; Strong analytical skills with the ability to compare options, justify rankings, and spot subtle issues; High attention to detail and commitment to training data quality, QA, and validation; Ability to follow detailed instructions and maintain annotation guidelines compliance; Comfortable working with confidential data and adhering to content safety labeling requirements.

Preferred Qualifications

Prior experience in AI data labeling, RLHF, LLM evaluation, prompt evaluation, or QA evaluation; Familiarity with large language model evaluation concepts (helpfulness, harmlessness, truthfulness, and style); Experience writing concise, well-structured rationales that demonstrate clear reasoning; Self-driven, reliable, and able to manage productivity in a fully remote environment; Interest in improving model performance improvement through iterative feedback and quality-focused workflows.

How to Apply

Apply through Rexzone with your resume/CV and a brief note confirming you are based in Germany and fluent in English and German. If selected, you will complete a short qualification and calibration process focused on ranking, reasoning, and annotation guidelines compliance.

Frequently Asked Questions

  • Q: Is this role remote?

    Yes. This is a full-time remote role, and you must be based in Germany.

  • Q: What tasks will I do?

    You will perform large language model evaluation work including evaluation, ranking, QA evaluation, validation, prompt evaluation, data labeling, content safety labeling, and writing rationales to support RLHF and training data quality.

  • Q: Do I need AI experience?

    AI/annotation experience is preferred but not required. You must be able to follow annotation guidelines compliance, apply strong analytical skills, and produce consistent reasoning for rankings and QA decisions.

  • Q: What languages are required?

    Fluency in both German and English is required for bilingual evaluation and writing.

  • Q: What domains are covered?

    You will evaluate a wide range of general-domain content, including helpfulness, safety, factuality, style, and instruction-following, to improve training data quality and model performance improvement.

230+Domains Covered
120K+PhD, Specialist, Experts Onboarded
50+Countries Represented

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