Germany-Based English & German AI Generalist Trainer (Remote, Full-Time) 2026 May
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About Rex.zone
Rex.zone is hiring Germany-based bilingual (English/German) AI Generalist Trainers to support large language model evaluation through RLHF, ranking, and QA evaluation workflows that strengthen training data quality and drive model performance improvement.
About The Role
Evaluate and improve AI/LLM systems by assessing model outputs, ranking responses, and writing clear rationales. You will apply annotation guidelines compliance, validate edge cases, and perform QA evaluation to reduce errors and increase reliability.
Responsibilities
- Perform large language model evaluation of model-generated outputs in English and German
- Rank multiple responses using defined rubrics and reasoning standards
- Write concise rationales that justify selections and support RLHF learning signals
- Execute QA evaluation for correctness, consistency, and annotation guidelines compliance
- Validate ambiguous cases, identify policy gaps, and elevate issues with evidence
- Apply prompt evaluation for instruction-following, helpfulness, and factuality checks
- Support content safety labeling where required and document decisions for auditability
- Maintain training data quality by meeting throughput targets and inter-annotator consistency goals
Basic Qualifications
- Must be based in Germany and eligible to work remotely per local requirements
- Full professional fluency in English and German (reading and writing)
- Strong analytical reasoning and attention to detail
- Ability to follow rubric-based guidelines and explain decisions in writing
- Comfort with web-based tools, spreadsheets, and structured evaluation forms
Preferred Qualifications
- Experience in data labeling, RLHF, prompt evaluation, QA evaluation, or content safety labeling
- Familiarity with LLM behavior, failure modes, and evaluation concepts
- Background in linguistics, writing/editing, QA, support, research, or technical documentation
Compensation And Schedule
USD $35–$40 per hour depending on performance and project needs. Full-time, remote; task-based within defined quality thresholds with ongoing feedback.
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