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, 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 responses to the same prompt and justify the preferred output.
• Provide concise feedback to modeling and training teams on recurring failure patterns.
• Craft adversarial prompts to expose biased, harmful, or insecure model behavior.
• Collaborate with QA to refine evaluation guidelines and handle ambiguous edge cases.
• Participate in cross‑checking sessions to ensure inter‑rater reliability.
• Analyze underperforming outputs, hypothesize root causes, and flag novel model behaviors.

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.
• Strong understanding of prompt engineering and the ability to explain why a model output is good or bad.
• Experience with Reinforcement Learning from Human Feedback (RLHF) data collection and evaluation.
• Proven ability to maintain consistency across evaluation teams and conduct calibration sessions.

Required skills

• Prompt engineering
• RLHF data collection
• Dataset sourcing, cleaning, and annotation
• Data analysis
• A/B testing concepts
• Experiment design for model comparison