Germany-Based English & German AI Generalist Trainer 2026 May

Rexzone is hiring Germany-based, bilingual English/German AI Generalist Trainers to support RLHF and large language model evaluation by ranking model outputs, writing clear rationales, and enforcing annotation guidelines compliance to strengthen training data quality and drive model performance improvement.

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About the Role

As a Germany-based English & German AI Generalist Trainer at Rexzone, you will work remotely in AI/LLM workflows focused on RLHF, large language model evaluation, and training data quality. You will evaluate, rank, and QA model-generated outputs in both German and English, provide reasoning-rich rationales, and follow annotation guidelines compliance to support model performance improvement across multiple domains.

Key Responsibilities

Perform large language model evaluation by assessing response quality, factuality, relevance, and instruction-following; rank multiple model outputs and document decisions with clear reasoning; execute QA evaluation on labeled datasets to validate consistency and correctness; apply annotation guidelines compliance and flag edge cases, ambiguity, or safety issues; conduct prompt evaluation and error analysis to identify patterns impacting model behavior; validate training data quality through spot checks, adjudication, and discrepancy resolution; label and review tasks including data labeling, content safety labeling, and policy-aligned decisions in German and English; collaborate asynchronously with leads to calibrate scoring rubrics and improve evaluation reliability.

Basic Qualifications

Must be based in Germany and authorized to work as a remote contractor/employee as applicable; fluent in German and English (reading, writing, and reasoning); strong analytical skills with the ability to compare outputs and justify rankings; high attention to detail with consistent QA and validation habits; ability to follow annotation guidelines compliance precisely and maintain quality under time constraints; comfortable working with web-based labeling tools and structured rubrics; reliable internet connection and ability to work full-time remotely.

Preferred Qualifications

Prior experience in AI training data work such as data labeling, QA evaluation, prompt evaluation, or RLHF-style ranking; familiarity with LLM behavior, common failure modes, and large language model evaluation concepts; experience with content safety labeling or policy-driven decisions; strong writing skills for concise, evidence-based rationales; self-driven and able to work independently while maintaining calibration standards; experience improving training data quality via audits, adjudication, or guideline feedback.

Compensation

USD $35–$40 per hour, full-time, remote (Germany-based). Exact rate within range depends on demonstrated evaluation quality, bilingual proficiency, and task performance during calibration.

How to Apply

Apply to Rexzone with your resume/CV and a short note confirming Germany location and English/German fluency. If shortlisted, you will complete a brief qualification and calibration to assess evaluation, ranking, QA, and rationale-writing skills.

Frequently Asked Questions

  • Q: Is this role remote?

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

  • Q: What tasks will I do?

    You will perform large language model evaluation tasks such as evaluating and ranking model outputs, running QA evaluation and validation checks, doing prompt evaluation, writing reasoning-based rationales, and following annotation guidelines compliance to protect training data quality.

  • Q: Do I need AI experience?

    AI experience is preferred but not required. We look for strong analytical skills, attention to detail, and the ability to apply rubrics consistently; training and calibration are provided.

  • Q: What languages are required?

    Fluency in both German and English is required, including reading, writing, and explaining decisions clearly.

  • Q: What domains are covered?

    Domains vary by project and may include general knowledge, customer support-style conversations, content safety labeling, and instruction-following tasks, all aimed at training data quality and model performance improvement.

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

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