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Germany-Based English & German AI Generalist Trainer 2026 May

Rex.zoneApplies on LinkedInData & Analytics
Hiring from
Germany
Work type
Remote
Posted
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About The Role

As an AI Generalist Trainer at Rex.zone, you will evaluate and improve AI systems by reviewing model-generated responses in English and German. You will perform RLHF-style ranking, prompt evaluation, QA evaluation, and validation against policy and annotation guidelines to improve training data quality and model performance.

Responsibilities

  • Review prompts and model outputs in English and German
  • Rank and compare multiple model responses using RLHF-aligned criteria
  • Write concise, evidence-based rationales that justify evaluation decisions
  • Execute QA evaluation for annotation accuracy, consistency, and guidelines compliance
  • Label and categorize data, including content safety labeling when required
  • Validate edge cases, detect policy violations, and escalate ambiguous items with clear notes
  • Track common failure modes and propose rubric improvements
  • Maintain throughput while meeting accuracy targets and quality benchmarks

Basic Qualifications

  • Must be based in Germany and able to work remotely from Germany
  • Fluent in German and English (reading, writing, comprehension)
  • Strong analytical skills and attention to detail
  • Comfortable with structured tasks, feedback loops, and quality audits
  • Able to explain reasoning clearly and objectively in written rationales

Preferred Qualifications

  • Experience with AI data labeling, LLM evaluation, prompt evaluation, or QA evaluation
  • Familiarity with RLHF concepts and ranking tasks
  • Knowledge of content safety labeling (toxicity, policy compliance, sensitive content)
  • Self-driven and reliable in a remote environment

FAQ

Is this role remote?

Yes. This is a fully remote, full-time role, and you must be based in Germany.

Do I need AI experience?

AI experience is helpful but not required; strong analytical skills and consistent guideline-following matter most.

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