Key Responsibilities:

• Create, annotate, and evaluate complex training data sets in physics across multiple modalities, including text, images, and video.
• Act as a subject-matter expert in Classical Mechanics, Quantum Mechanics, and Statistical/Thermodynamic systems, guiding AI model development and learning.
• Craft clear, precise, and pedagogically sound explanations and problem solutions in diverse academic and instructional styles.
• Audit and improve AI-generated content, ensuring adherence to rigorous scientific and linguistic standards.
• Perform quality checks on tasks completed by other experts, ensuring consistency and accuracy in physics content.
• Collaborate closely with machine learning scientists and engineers to enhance data guidelines, identify edge cases, and optimize annotation tools.
• Troubleshoot data or guideline ambiguities, contributing high-judgment feedback to continuous process improvement efforts.

Required Skills and Qualifications:

• Master's or PhD in Physics or closely related field.
• Strong proficiency in English. Candidate must demonstrate excellent writing, reading, and comprehension skills (C2 level in the Common European Framework CEFR scale).
• Strong understanding of U.S.-based culture, society, and norms.
• Exceptional written and verbal communication skills, capable of explaining complex concepts clearly and concisely.
• Strong analytical skills and experience in data-intensive or research-focused environments.
• Meticulous attention to detail and the ability to follow (and help evolve) detailed guidelines.
• Demonstrated ability to work independently, exercising sound judgment in ambiguous or incomplete scenarios.

Preferred Qualifications:

• Familiarity with AI/ML concepts, or prior experience in AI model training or evaluation.
• Proficiency in Python, LaTeX, or scientific computing tools such as Mathematica or Jupyter.
• Experience with data annotation, prompt engineering, or language model fine-tuning.