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 QA evaluation—improving training data quality and driving model performance improvement via consistent ranking, validation, and annotation guidelines compliance.

About the Role

As a Germany-based English & German AI Generalist Trainer at Rexzone, you will evaluate model-generated outputs across common user scenarios and help improve AI/LLM workflows. Your work will focus on RLHF-style preference ranking, large language model evaluation, and training data quality initiatives. You will apply annotation guidelines compliance, write clear rationales, and conduct QA evaluation to support model performance improvement. This is a full-time remote role requiring bilingual fluency in German and English.

Responsibilities

Evaluate and compare model-generated responses in German and English using defined rubrics; Rank outputs for RLHF datasets and document reasoning/rationales for preference decisions; Perform prompt evaluation and QA evaluation to identify inconsistencies, factual errors, or policy violations; Validate labeled data for training data quality, including edge-case handling and guideline adherence; Apply annotation guidelines compliance and escalate ambiguous cases with well-structured notes; Conduct content safety labeling and ensure safe-completion standards are met; Review peer work, provide calibrated feedback, and support ongoing quality improvement; Track recurring error patterns and propose rubric or guideline clarifications for model performance improvement.

Basic Qualifications

Based in Germany and authorized to work from Germany; Fluent in German and English (written and reading comprehension required for detailed evaluations); Strong analytical skills with the ability to weigh tradeoffs and justify rankings with clear reasoning; High attention to detail and consistency when following rubrics and annotation guidelines compliance; Comfortable working with ambiguous tasks and applying policy/rubric judgment; Reliable internet connection and ability to meet quality and throughput targets in a remote setting.

Preferred Qualifications

Experience with data labeling, content safety labeling, or QA evaluation in AI/ML programs; Familiarity with LLM evaluation concepts (e.g., RLHF, preference ranking, prompt evaluation); Background in linguistics, translation, writing, research, or quality assurance; Self-driven, organized, and comfortable owning tasks end-to-end with minimal supervision; Experience working with annotation tools and structured feedback loops for training data quality.

Pay And Employment Details

Full-time, remote. Compensation is $35–$40 USD per hour depending on assessment results and role alignment. You will contribute directly to large language model evaluation, training data quality, and model performance improvement for Rexzone clients.

How to Apply

Apply with an up-to-date resume/CV and a brief note describing your experience evaluating written content in German and English. Highlight any work involving data labeling, QA evaluation, prompt evaluation, or annotation guidelines compliance. Rexzone reviews applications on a rolling basis.

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 perform large language model evaluation tasks such as evaluating outputs, ranking responses for RLHF, writing reasoning-based rationales, completing QA evaluation, and validating training data quality against annotation guidelines.
Q: Do I need AI experience?
AI experience is helpful but not required. If you can follow rubrics, apply annotation guidelines compliance, and provide consistent evaluations with clear reasoning, you can succeed. Prior data labeling or evaluation experience is a plus.
Q: What languages are required?
Fluency in both German and English is required, as you will evaluate and compare content in both languages.
Q: What domains are covered?
You may evaluate general knowledge, customer support-style prompts, writing quality, reasoning, safety and policy adherence, and other everyday use cases relevant to prompt evaluation, content safety labeling, and model performance improvement.

230+Domains Covered

120K+PhD, Specialist, Experts Onboarded

50+Countries Represented

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