Germany-Based English & German AI Generalist Trainer (Remote, Full-Time) 2026 May

Rexzone is hiring Germany-based English/German AI Generalist Trainers to improve AI/LLM systems through RLHF-style ranking, large language model evaluation, and training data quality work, including prompt evaluation, QA evaluation, and rationale writing to drive model performance improvement.

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About the Role

As a Germany-based English & German AI Generalist Trainer at Rexzone, you will evaluate and rank model-generated outputs across diverse prompts to support large language model evaluation and model performance improvement. You will follow annotation guidelines compliance, perform QA evaluation, and produce clear reasoning rationales that strengthen training data quality within RLHF and related evaluation workflows.

Responsibilities

Perform large language model evaluation by reviewing, ranking, and scoring model outputs against defined rubrics; write concise reasoning rationales explaining rankings and decisions in English and German; execute QA evaluation and validation checks to ensure training data quality and annotation guidelines compliance; conduct prompt evaluation for helpfulness, correctness, safety, and policy adherence, including content safety labeling when required; identify edge cases, ambiguity, and failure patterns, and escalate issues with clear evidence for model performance improvement; apply data labeling standards consistently, track disagreements, and support calibration through example-based discussions; validate task inputs/outputs for completeness, formatting, and alignment with project requirements.

Basic Qualifications

Based in Germany and legally able to work remotely from Germany; fluent in English and German (reading and writing) with strong grammar and professional communication; strong analytical skills with the ability to evaluate evidence, compare outputs, and justify rankings; excellent attention to detail and consistency to maintain training data quality; comfort working with written guidelines, rubrics, and iterative feedback cycles; reliable availability for full-time remote work and the ability to meet deadlines.

Preferred Qualifications

Prior experience in AI data labeling, annotation, or evaluation (including RLHF, LLM evaluation, prompt evaluation, or QA evaluation); familiarity with common LLM behaviors and limitations (hallucinations, safety issues, instruction following); experience applying annotation guidelines compliance in high-volume workflows; self-driven, organized, and proactive in clarifying ambiguity and improving process quality; interest in content safety labeling, policy-based evaluation, and systematic validation methods.

Pay Range

USD $35–$40 per hour (hourly), depending on skills and project needs.

How to Apply

Apply to Rexzone with a brief summary of your bilingual English/German experience, your Germany location, and any background in evaluation, data labeling, or QA. Shortlisted candidates will complete an assessment focused on ranking, reasoning, and annotation guidelines compliance.

Frequently Asked Questions

  • Q: Is this role remote?

    Yes. This is a remote, full-time role for candidates based in Germany.

  • Q: What tasks will I do?

    You will evaluate and rank model-generated outputs, perform QA evaluation and validation, follow annotation guidelines compliance, complete prompt evaluation, and write reasoning rationales to improve training data quality and model performance improvement.

  • Q: Do I need AI experience?

    AI/annotation experience is helpful but not required. You must be strong in analytical reasoning, attention to detail, and consistent rubric-based evaluation; training is provided for project-specific workflows.

  • Q: What languages are required?

    Fluency in both English and German is required, as tasks involve bilingual evaluation and rationale writing.

  • Q: What domains are covered?

    Domains vary by project and may include general knowledge, customer support-style queries, writing quality, reasoning tasks, and content safety labeling, all within large language model evaluation and RLHF-style workflows.

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

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