LLM Evaluator (Model Response Analyst)

About the role

We are looking for a detail‑oriented LLM Evaluator (Model Response Analyst) to join our remote team. In this position you will assess the quality of large language model outputs, identify failures, and help improve model safety and performance.

Key responsibilities

• Evaluate and rank model‑generated text using complex rubrics covering factuality, coherence, safety, instruction‑following and creativity.
• Compare multiple responses to the same prompt, select the preferred output and provide clear justifications.
• Provide feedback to modeling and training teams on recurring failure patterns.
• Design adversarial prompts to expose biased, harmful or insecure model behavior.
• Collaborate with QA to refine evaluation guidelines and resolve ambiguous cases.
• Participate in cross‑checking sessions to calibrate scoring and ensure inter‑rater reliability.
• Analyze under‑performing outputs, hypothesize root causes and flag novel behaviors for research.

Required profile

• At least 2 years of professional experience in computational linguistics, data analysis, technical writing, NLP quality assurance or related fields.
• Bachelor’s degree in computer science or a related discipline.
• Proven ability to craft prompts that test model limits and to explain why an output is good or bad.
• Experience with Reinforcement Learning from Human Feedback (RLHF) data collection and evaluation.
• Familiarity with IAA scoring, calibration sessions and A/B testing for AI models.

Required skills

• Prompt engineering
• Reinforcement Learning from Human Feedback (RLHF)
• IAA score analysis
• A/B testing concepts
• Dataset sourcing, cleaning and annotation
• Computational linguistics
• Data analysis