Germany-Based English & German AI Generalist Trainer 2026 May

Rexzone is hiring Germany-based, remote, full-time AI Generalist Trainers to support RLHF and large language model evaluation by assessing, ranking, and validating model outputs. You will apply annotation guidelines compliance to improve training data quality, document reasoning, and drive model performance improvement across English and German workflows. This role focuses on LLM evaluation, prompt evaluation, QA evaluation, and content safety labeling to help teams ship safer, more accurate AI systems.

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About the Role

As a Germany-based English & German AI Generalist Trainer at Rexzone, you will evaluate model-generated responses, rank alternatives, write clear rationales, and perform validation checks that improve training data quality. Your work directly supports RLHF pipelines, large language model evaluation, and model performance improvement through consistent application of annotation guidelines compliance.

Responsibilities

Evaluate and rank model-generated outputs in English and German using defined rubrics and annotation guidelines. Perform QA evaluation on labeled datasets to validate consistency, completeness, and policy adherence. Write concise reasoning and rationales that justify rankings and identify failure modes. Validate prompt-response pairs, detect hallucinations, and flag safety and compliance issues. Apply content safety labeling and ensure annotation guidelines compliance across domains. Collaborate asynchronously with remote reviewers to resolve edge cases and improve rubrics. Track errors, suggest rubric updates, and contribute to model performance improvement initiatives. Maintain high throughput while meeting training data quality targets and review SLAs.

Basic Qualifications

Must be based in Germany and eligible to work as a remote contractor/employee per local requirements. Fluency in English and German (reading and writing) with the ability to evaluate nuanced tone and intent. Strong analytical skills and structured thinking for comparative evaluation and ranking tasks. High attention to detail and consistent adherence to annotation guidelines compliance. Comfort working with web-based labeling tools, spreadsheets, and written QA checklists. Ability to explain reasoning clearly and consistently in written rationales.

Preferred Qualifications

Prior experience in data labeling, QA evaluation, content moderation, or annotation operations. Familiarity with RLHF concepts and large language model evaluation practices. Experience with prompt evaluation, rubric-based ranking, and error taxonomy creation. Self-driven, reliable, and able to manage workload independently in a remote setting. Interest in improving training data quality and contributing to model performance improvement.

Compensation and Schedule

Pay: $35–$40 USD per hour (hourly). Full-time, remote. Work is performed from Germany with bilingual English/German task requirements.

How to Apply

Apply through Rexzone with your resume/CV and a brief note highlighting bilingual English/German experience, analytical evaluation work, and any LLM evaluation or data labeling exposure.

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 evaluate and rank model outputs, perform QA evaluation and validation, write reasoning-based rationales, follow annotation guidelines, and complete content safety labeling as needed to improve training data quality.

  • Q: Do I need AI experience?

    AI experience is helpful but not required. Strong analytical skills, attention to detail, and the ability to follow annotation guidelines compliance are essential; we provide task instructions and rubrics.

  • Q: What languages are required?

    Fluency in both English and German is required for bilingual large language model evaluation and prompt evaluation tasks.

  • Q: What domains are covered?

    Tasks can span general knowledge, customer support-style interactions, safety and policy scenarios, reasoning and instruction-following, and other domains relevant to model performance improvement.

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

Industry-Leading Compensation

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