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Evaluate and refine the behavior of large language models in physics contexts by writing prompts, assessing conceptual accuracy, and conducting fact-checking against authoritative sources. This role involves annotating model responses and applying consistent evaluation standards.
Responsibilities
- Write and refine prompts to guide model behavior in physics contexts
- Evaluate LLM-generated responses to physics-related queries for conceptual accuracy and reasoning quality
- Conduct fact-checking using authoritative public sources and domain knowledge
- Annotate model responses by identifying strengths and areas of improvement
- Assess clarity, structure, and appropriateness of explanations for different audiences
- Apply consistent evaluation standards by following clear taxonomies and benchmarks
Requirements
- PhD in Physics or closely related field
- Deep expertise in Classical Mechanics & Dynamics, Electromagnetism, Thermodynamics, Quantum Physics, or Relativity
- Significant experience using large language models (LLMs)
- Excellent writing skills and ability to explain complex physics concepts
- Strong attention to detail and experience reviewing technical writing
Qualifications
- PhD in Physics or closely related field
Nice to Have
- Experience with RLHF, model evaluation, or data annotation work
- Experience teaching or explaining physics concepts to non-experts
- Familiarity with evaluation rubrics or structured review frameworks
Skills
LLMs
*
* Required skills
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