Physics QA Lead - Remote
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Key skills for this role
About the Role
YO IT Consulting is seeking a Physics QA Lead to oversee quality and trainer performance on physics AI training projects. You will review AI-generated physics content, provide feedback, and ensure adherence to quality standards.
Key Skills for This Role
Responsibilities
- Spot check physics items, identify quality issues, provide feedback through DMs, and escalate recurring or critical issues.
- Review AI generated physics explanations, calculations, diagrams, derivations, experimental interpretations, and step by step reasoning.
- Update trainers/QAs on Discord about guidelines, workflow updates, and physics specific quality expectations.
- 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
- Bachelor’s, Master’s, or PhD degree in Physics, Applied Physics, Engineering Physics, Astrophysics, Mathematics, Engineering, or a closely related quantitative/scientific field.
- 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.
- Strong understanding of classical mechanics, electromagnetism, waves, optics, thermodynamics, statistical mechanics, quantum mechanics, relativity, units, dimensional analysis, and mathematical modeling.
- 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.
- Highly organized and able to 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.
Full Job Posting
About This 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.
- You will review AI generated physics content and trainer/QA work, evaluate output quality against project guidelines, provide precise written feedback, and ensure contributors follow expected quality standards.
- This role requires strong physics expertise, strong English communication skills, excellent attention to detail, structured communication, and the ability to manage quality workflows across remote teams.
- Important: There is no immediate project for this role; however, if qualified, you will be among the first experts we reach out to when relevant opportunities arise.
Your Profile
- Bachelor’s, Master’s, or PhD degree in Physics, Applied Physics, Engineering Physics, Astrophysics, Mathematics, Engineering, or a closely related quantitative/scientific field.
- 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.
- Strong understanding of classical mechanics, electromagnetism, waves, optics, thermodynamics, statistical mechanics, quantum mechanics, relativity, units, dimensional analysis, and mathematical modeling.
- 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.
- Highly organized and able to 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.
Key Responsibilities
- Spot check physics items, identify quality issues, provide feedback through DMs, and escalate recurring or critical issues.
- Review AI generated physics explanations, calculations, diagrams, derivations, experimental interpretations, and step by step reasoning.
- Update trainers/QAs on Discord about guidelines, workflow updates, and physics specific quality expectations.
- 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.
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