Germany-Based English & German AI Generalist Trainer (Remote, Full-Time) 2026 May

Rexzone is hiring Germany-based, bilingual (English/German) AI Generalist Trainers to support RLHF, large language model evaluation, and training data quality through structured evaluation, ranking, QA evaluation, and rationale writing to drive model performance improvement.

About the Role

As a Germany-based English & German AI Generalist Trainer at Rexzone, you will evaluate and improve AI systems by assessing model-generated outputs across bilingual tasks. Your work supports RLHF workflows and large language model evaluation by applying annotation guidelines, performing prompt evaluation, and ensuring training data quality. You will rank responses, validate reasoning, and document rationales that enable model performance improvement while maintaining annotation guidelines compliance.

Key Responsibilities

Execute large language model evaluation by reviewing English and German prompts and responses; perform RLHF-style ranking of multiple outputs against defined rubrics; conduct QA evaluation to detect errors, policy risks, and inconsistencies; write clear rationales that explain reasoning behind rankings and decisions; validate labels and evaluations for training data quality and annotation guidelines compliance; perform prompt evaluation and targeted checks for content safety labeling; escalate edge cases, ambiguous instructions, and guideline conflicts with evidence; collaborate asynchronously with reviewers to resolve disagreements and improve evaluation consistency.

Basic Qualifications

Based in Germany and authorized to work as a remote contractor/employee per Rexzone requirements; fluent in German and English (reading and writing) with strong grammar and comprehension; strong analytical skills for comparing outputs, identifying logical flaws, and evaluating reasoning; exceptional attention to detail for consistent labeling and annotation guidelines compliance; ability to follow rubrics, document decisions, and maintain training data quality across repetitive tasks; reliable internet connection and ability to work full-time with consistent availability.

Preferred Qualifications

Prior experience in data labeling, RLHF, or LLM evaluation (or related QA/review roles); familiarity with LLM behavior (hallucinations, bias, instruction-following, safety) and how evaluation impacts model performance improvement; experience writing structured rationales and applying multi-criteria rubrics; comfort handling sensitive topics and performing content safety labeling; self-driven, organized, and able to work independently in a remote environment with minimal supervision.

Compensation and Work Setup

Remote (Germany-based). Full-time. Pay range: $35–$40 USD per hour. You will complete evaluation and ranking tasks, QA checks, and validation within defined quality standards to support training data quality and model performance improvement.

How to Apply

Apply to Rexzone with a short summary of your bilingual English/German experience, availability in Germany, and any relevant evaluation, QA, or annotation background. Highlight examples where you applied guidelines, performed structured reasoning, or improved quality in review workflows.

Frequently Asked Questions

Q: Is this role remote?
Yes. This is a remote, full-time role, and you must be based in Germany.
Q: What tasks will I do?
You will perform large language model evaluation tasks including prompt evaluation, ranking model outputs (RLHF-style), QA evaluation, validation of labels, and writing rationales to support training data quality and model performance improvement.
Q: Do I need AI experience?
AI experience is preferred but not required. Strong analytical skills, attention to detail, and the ability to follow annotation guidelines compliance are essential; training is provided on rubrics and workflows.
Q: What languages are required?
Fluency in both German and English is required, including strong reading and writing skills in both languages.
Q: What domains are covered?
You may evaluate general knowledge, instruction following, reasoning, helpfulness, and content safety labeling scenarios, using defined rubrics to ensure consistent training data quality.

230+Domains Covered

120K+PhD, Specialist, Experts Onboarded

50+Countries Represented

Industry-Leading Compensation

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