Physics QA Lead - Remote

About the role

In this hourly, remote contractor role, you will work as a Physics Quality Assurance Lead to oversee quality, consistency, and trainer performance across physics AI training projects.

Responsibilities

• Review AI-generated physics content and trainer/QA work, evaluating output quality against project guidelines and providing precise written feedback.
• Evaluate work for scientific accuracy, physical reasoning, calculation correctness, unit consistency, formula use, conceptual clarity, experimental understanding, formatting, instruction-following, and adherence to project-specific rubrics.
• Assess work for recurring quality issues, communicate updates to trainers and QAs, support onboarding, maintain documentation, and help activate contributors who are not working consistently.
• Spot recurring quality issues, communicate updates to trainers and QAs, support onboarding, maintain documentation, and help activate contributors who are not working consistently.
• Respond to questions around physical assumptions, formulas, units, derivations, diagrams, experimental setups, and rubric interpretation.
• DM inactive contributors, encourage activation, track follow-ups, and flag availability issues.
• Create and maintain physics documentation, style guides, trackers, FAQs, examples, honeypots, and onboarding materials.
• Run onboarding/training calls for physics contributors, flag misleading, numerically incorrect, physically impossible, unsafe, or poorly contextualized physics claims.
• Identify recurring quality gaps and improve physics QA workflows.

Requirements

Your profile should include:

• A bachelor’s, master’s, or PhD degree in Physics, Applied Physics, Engineering Physics, Astrophysics, Mathematics, Engineering, or a closely related quantitative/scientific field.
• A strong grasp of the English language to follow guidelines, communicate with teams, and provide clear technical feedback.
• 3+ years of experience in physics research, teaching, tutoring, laboratory work, science writing, academic review, engineering analysis, or related scientific workflows.
• A strong understanding of classical mechanics, electromagnetism, waves, optics, thermodynamics, statistical mechanics, quantum mechanics, relativity, units, dimensional analysis, and mathematical modeling.
• The ability to evaluate physics content against rubrics and identify issues such as incorrect assumptions, wrong formulas, unit errors, flawed reasoning, sign convention mistakes, physically impossible claims, or misleading explanations.
• Familiarity with tools or methods such as Python, MATLAB, Mathematica, LaTeX, laboratory methods, data analysis, simulations, scientific visualization, and numerical methods is preferred.
• Experience leading or supporting remote teams of educators, reviewers, researchers, annotators, science writers, or QAs is strongly preferred.
• Comfortable with Discord, Google Sheets, Google Docs, trackers, dashboards, and project management systems.
• A highly organized individual who can maintain style guides, FAQs, trackers, onboarding materials, honeypots, calibration tasks, and documentation.
• Experience with AI training, data annotation, LLM evaluation, scientific QA, academic review, or rubric-based review is a strong plus.