Germany-Based English & German AI Generalist Trainer 2026 May

Rexzone is hiring Germany-based AI Generalist Trainers to support large language model evaluation through RLHF, prompt evaluation, and training data quality workflows. You will assess and rank model outputs in English and German, perform QA evaluation, and write clear rationales that drive model performance improvement while ensuring annotation guidelines compliance.

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About the Role

As a Germany-based English & German AI Generalist Trainer at Rexzone, you will work remotely and full-time to evaluate, rank, and validate model-generated responses used in RLHF and large language model evaluation pipelines. Your work directly impacts training data quality, annotation guidelines compliance, and model performance improvement. You will apply consistent reasoning, follow detailed rubrics, and complete QA evaluation to ensure high-quality training signals across English and German tasks.

Responsibilities

Evaluate and rank model-generated outputs against defined criteria; perform prompt evaluation, QA evaluation, and validation checks for training data quality; write concise rationales that explain reasoning and support model performance improvement; apply annotation guidelines compliance consistently across English and German content; identify edge cases, content safety labeling needs, and policy violations, and escalate with clear evidence; run self-checks and peer-review style QA to reduce errors and improve labeling consistency; track task feedback and suggest rubric clarifications that improve large language model 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 comprehension); strong analytical skills with the ability to compare alternatives and justify rankings; high attention to detail and ability to follow annotation guidelines compliance requirements; comfort working with web tools, spreadsheets, and structured evaluation forms; ability to meet quality targets and throughput expectations in a full-time remote setting.

Preferred Qualifications

Experience with data labeling, content evaluation, or QA evaluation workflows; familiarity with RLHF, LLM evaluation, prompt evaluation, or related AI/ML concepts; demonstrated ability to produce consistent reasoning and clear written rationales; self-driven, organized, and reliable in a remote environment; exposure to content safety labeling or policy-based review processes.

Compensation

USD $35–$40 per hour, paid hourly. Full-time, remote.

How to Apply

Apply through Rexzone with a brief summary of your bilingual (English/German) experience, availability for full-time remote work in Germany, and any background in evaluation, QA, or data labeling. Include writing samples if available that demonstrate clear reasoning and decision-making.

Skills Used in This Role

RLHF; large language model evaluation; LLM evaluation; data labeling; prompt evaluation; QA evaluation; annotation guidelines; annotation guidelines compliance; training data quality; content safety labeling; ranking; validation; reasoning; rubric-based evaluation; quality assurance; bilingual evaluation (English/German).

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 evaluate and rank model outputs, perform QA evaluation and validation, follow annotation guidelines compliance rules, and write rationales that improve training data quality and model performance improvement in RLHF workflows.

  • Q: Do I need AI experience?

    AI experience is helpful but not required. We provide guidelines and rubrics; however, prior work in data labeling, evaluation, or quality assurance can be an advantage.

  • Q: What languages are required?

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

  • Q: What domains are covered?

    Tasks may include general knowledge, instruction following, writing quality, reasoning quality, and content safety labeling, all within large language model evaluation and prompt evaluation workflows.

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

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