LLM Annotator - Master's Degree
We are seeking highly motivated LLM Annotators to support the evaluation and improvement of cutting-edge Large Language Models (LLMs).
Hiring companyTuring
About the role
In this role, you will analyze structured data, create challenging prompts, evaluate AI-generated responses for factual accuracy and reasoning quality, and provide evidence-backed feedback to improve model performance.
We are looking for curious, detail-oriented professionals who enjoy solving complex problems and evaluating AI systems. The ideal candidate can analyze data, think critically, validate responses against evidence, and clearly articulate why a model's output is correct or incorrect. Experience working with AI models and creating challenging evaluation prompts is a strong advantage.
Employment type: Contractor assignment (no medical/paid leave).
Benefits
- Opportunity to work on cutting-edge AI projects.
- Competitive compensation.
- Flexible working hours and remote work environment.
Responsibilities
- Create challenging prompts that evaluate an LLM's ability to retrieve, analyze, and reason over structured data.
- Assess AI-generated responses for factual accuracy, logical reasoning, and completeness.
- Identify model failures, inconsistencies, hallucinations, and reasoning gaps.
- Validate model outputs using provided datasets and supporting evidence.
- Document findings with clear, evidence-based explanations.
- Consistently follow annotation guidelines and maintain high-quality standards.
Preferred skills
- Experience working with Large Language Models (LLMs) or Generative AI.
- Familiarity with prompt engineering, AI evaluation, data annotation, or model testing.
- Experience working with structured datasets (CSV, Excel, databases, etc.).
- Ability to identify edge cases and design prompts that expose model limitations.
Experience and education
- Master's degree or higher in any discipline.
- Minimum 3 years of professional, research, or teaching experience.
- Strong analytical and critical thinking skills.
- Exceptional attention to detail and ability to validate information against source data.
Language requirements
- Excellent written English communication skills.
Assessment requirements
Shortlisting based on qualifications and assessment scores.
Schedule details
Commitments Required: 40, 30 or 20 hours per week with at least 4 hours PST overlap.
Duration of contract: 4 weeks.
Eligibility
Work arrangement: Fully remote
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