LLM Evaluator – Model Response Analyst (Remote)

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, you will analyze AI‑generated text for factual accuracy, coherence, safety, bias and alignment with our 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 provide clear justifications.
• Provide concise feedback to modeling and training teams on 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 participate in cross‑checking sessions to ensure inter‑rater reliability.
• Investigate under‑performing outputs, hypothesize root causes and flag novel model behaviors for research.
• Assist in designing experiments and A/B tests to verify improvements in new model versions.

Required profile

• Minimum 2 years of professional experience in computational linguistics, data analysis, technical writing, NLP QA 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 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 understanding of data distribution impacts.

Required skills

• Prompt engineering
• RLHF data collection
• Dataset annotation and cleaning
• A/B testing for AI models
• Experiment design and evaluation