RE

Germany-Based English & German AI Generalist Trainer (May 2026)

RemoExpertsApplies on LinkedInData & Analytics
Hiring from
Germany
Work type
Remote
Posted
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About The Role

As a Germany-based English & German AI Generalist Trainer at Rex.zone, you will evaluate and improve AI/LLM systems through RLHF-style feedback workflows. You will assess, rank, and QA model-generated responses in both German and English, document reasoning, and ensure annotation guidelines compliance to strengthen training data quality and enable model performance improvement. This is a remote, full-time role focused on large language model evaluation, prompt evaluation, and training data quality validation.

Key Responsibilities

  • Review, score, and rank model outputs across German and English datasets
  • Write concise, evidence-based rationales explaining preferences and reasoning
  • Execute QA evaluation to validate labels, resolve edge cases, and flag inconsistencies
  • Follow annotation guidelines and maintain high training data quality
  • Conduct prompt evaluation and content safety labeling when required
  • Escalate ambiguous cases, propose guideline improvements, and support calibration for consistency

Basic Qualifications

  • Based in Germany (remote) and able to work as required for the role
  • Fluent in German and English (reading, writing, and critical reasoning)
  • Strong analytical skills and ability to compare answers and justify rankings
  • Exceptional attention to detail and consistent guideline adherence
  • Comfort with structured rubrics, QA checklists, and high-throughput evaluation queues

Preferred Qualifications

  • Experience with data labeling, RLHF, prompt evaluation, or LLM evaluation
  • Familiarity with LLM failure modes (hallucinations, instruction-following issues, safety/policy violations)
  • Experience with calibration sessions and training data quality programs
  • Self-driven time management in a remote environment

How To Apply

Apply through Rex.zone with a brief summary of your bilingual (German/English) experience and any relevant evaluation, data labeling, or QA background.

Selected candidates may complete a short skills assessment focused on ranking, reasoning, and annotation guidelines compliance.

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