Germany-Based English & German AI Generalist Trainer 2026 May

Rexzone is hiring Germany-based AI Generalist Trainers to support AI/LLM workflows through RLHF, large language model evaluation, and training data quality improvement. You will assess, rank, and QA model-generated outputs in English and German, write clear rationales, and follow annotation guidelines compliance to drive model performance improvement across real-world tasks.

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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 model outputs, ranking alternatives, and documenting reasoning. Your work directly supports RLHF pipelines, large language model evaluation, and training data quality. You will apply annotation guidelines compliance, perform validation and QA evaluation, and help drive model performance improvement through consistent, high-quality judgments.

Responsibilities

Perform large language model evaluation by reviewing model-generated responses in English and German; Rank multiple outputs using RLHF-style preference ranking and clear scoring rubrics; Write concise, evidence-based rationales explaining reasoning behind rankings and decisions; Execute QA evaluation by checking labels for consistency, completeness, and guideline adherence; Validate edge cases, resolve ambiguities, and flag policy or instruction issues for guideline updates; Apply annotation guidelines compliance to ensure training data quality across tasks and domains; Conduct prompt evaluation and content safety labeling to support safe, reliable model behavior; Track errors, document patterns, and suggest process improvements that contribute to model performance improvement.

Basic Qualifications

Must be based in Germany with authorization to work; Fluent in German and English (reading and writing required for evaluation); Strong analytical skills with the ability to compare options, detect subtle issues, and justify decisions; High attention to detail and ability to follow annotation guidelines compliance consistently; Comfortable working independently in a remote setting with reliable internet and secure work habits.

Preferred Qualifications

Prior experience in AI data labeling, content moderation, QA, or evaluation workflows; Familiarity with LLM evaluation, RLHF concepts, and prompt evaluation; Experience writing structured rationales and applying rubrics for ranking and validation; Self-driven, organized, and able to manage throughput while maintaining training data quality.

Compensation and Work Type

Remote, Full-Time role based in Germany. Pay range is $35–$40 USD per hour, depending on assessment outcomes, quality, and role alignment. This position focuses on training data quality, evaluation, and QA that supports model performance improvement.

How to Apply

Apply to Rexzone with an up-to-date resume highlighting bilingual English/German work, analytical evaluation experience, and any AI/annotation exposure. Include brief examples of structured reasoning, ranking decisions, or QA work that demonstrate attention to detail and guideline adherence.

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, ranking and preference judgments (RLHF-style), QA evaluation, validation checks, prompt evaluation, and write rationales to support training data quality and model performance improvement.

  • Q: Do I need AI experience?

    AI or annotation experience is preferred but not required. Strong analytical skills, attention to detail, and consistent annotation guidelines compliance are required.

  • Q: What languages are required?

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

  • Q: What domains are covered?

    Generalist domains may include everyday knowledge, customer support-style queries, reasoning tasks, summarization, rewriting, content safety labeling, and other scenarios used in RLHF and LLM evaluation workflows.

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

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