LLM Evaluator (Model Response Analyst)

About the role

We are looking for a detail‑oriented LLM Evaluator (Model Response Analyst) to assess and improve the performance of large language models. Working remotely with a global team, you will analyze AI‑generated text for factual accuracy, coherence, safety, bias and alignment with guidelines.

Key responsibilities

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

Required profile

• Minimum 2 years of professional experience in computational linguistics, data analysis, technical writing, NLP quality assurance or cognitive science.
• Bachelor’s degree in Computer Science or a related field.
• Proven ability to craft prompts that test model limits and to explain why a response is good or bad.
• Experience with Reinforcement Learning from Human Feedback (RLHF) data collection and evaluation.
• Familiarity with dataset sourcing, cleaning, annotation and A/B testing for AI models.

Required skills

• Prompt engineering
• RLHF data collection
• Dataset annotation
• A/B testing for AI models
• Evaluation rubric development