LLM Evaluator – Model Response Analyst (Remote)

About the role

We are looking for a detail‑oriented LLM Evaluator to assess and improve the performance of large language models. You will work remotely with a global team, reviewing AI‑generated content for accuracy, coherence, safety, bias, and alignment with our guidelines.

Key responsibilities

• Evaluate and rank model‑generated text using complex rubrics covering factuality, coherence, safety, instruction‑following, and creativity.
• Compare multiple model responses to the same prompt and justify the preferred output.
• Provide concise feedback to modeling and training teams about recurring failure patterns.
• Design adversarial prompts to expose biased, harmful, or insecure model behavior.
• Collaborate with QA to refine evaluation guidelines for ambiguous or edge‑case scenarios.
• Participate in cross‑checking sessions to ensure inter‑rater reliability.
• Analyze underperforming outputs, hypothesize root causes, and flag novel 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 experience with Reinforcement Learning from Human Feedback (RLHF) data collection.
• Ability to explain why a model output is good or bad based on logic, tone, factuality, and instruction adherence.
• Experience monitoring and improving consistency among evaluation teams.

Required skills

• Prompt engineering for LLMs
• Dataset sourcing, cleaning, and annotation for model fine‑tuning or evaluation
• Understanding of data distribution impact on model performance
• Familiarity with A/B testing concepts applied to AI
• Designing experiments to compare model versions