Physics Quality Assurance Lead

About OpenTrain

OpenTrain is the #1 platform for finding and building careers in AI training and data labeling. OpenTrain AI hires and contracts contributors for specialized projects where human expertise helps improve the quality, reliability, and usefulness of artificial intelligence.

• Remote contractor work in a fast-growing AI industry
• Opportunities to apply specialized knowledge to cutting-edge AI systems
• Free OpenTrain account for building your AI training career

About AI Training and Scientific Quality Assurance

AI training depends on people who review examples, evaluate model outputs, and provide clear feedback. In this role, your physics expertise will help identify inaccurate explanations, flawed calculations, and misleading scientific reasoning so AI systems can produce more dependable physics content.

• Human evaluation is central to improving modern AI models
• Physics reviewers help assess both final answers and the reasoning behind them
• Your feedback will support consistent, rubric-based training quality

The Physics Quality Assurance Lead Role

OpenTrain AI is seeking a Physics Quality Assurance Lead to review AI-generated physics content and trainer QA work across physics training projects. You will assess scientific accuracy, physical reasoning, calculation correctness, unit consistency, formula use, conceptual clarity, formatting, and instruction-following.

You will also help strengthen project operations by identifying recurring quality issues, coordinating guideline updates, supporting onboarding, maintaining documentation, running training calls for physics contributors, and helping activate contributors who are not working consistently.

• Remote contractor position
• U.S. hiring only
• Part-time engagement with a 20+ hour weekly expectation
• Pay of up to $75 per hour

What You'll Do

You will evaluate physics work against project guidelines and project-specific rubrics, then provide precise written feedback that helps trainers, QAs, and contributors meet expected standards.

• Review physics explanations, calculations, diagrams, derivations, experimental interpretations, and step-by-step reasoning
• Identify incorrect assumptions, wrong formulas, unit errors, flawed reasoning, sign convention mistakes, physically impossible claims, and misleading explanations
• Check dimensional analysis, unit consistency, mathematical modeling, and physical plausibility
• Coordinate workflow changes and physics-specific quality expectations with trainers and QAs
• Maintain style guides, FAQs, trackers, examples, honeypots, onboarding materials, and other QA documentation
• Support contributor activation and follow up on availability issues
• Run training calls and help onboard physics contributors

Required Qualifications

This role requires a strong foundation in physics and the ability to communicate technical feedback clearly in English. Your background may come from research, teaching, tutoring, laboratory work, science writing, academic review, engineering analysis, or related scientific workflows.

• Degree in Physics, Applied Physics, Engineering Physics, Astrophysics, Mathematics, Engineering, or a closely related quantitative field
• At least 3 years of experience in physics research, teaching, tutoring, laboratory work, science writing, academic review, engineering analysis, or related scientific workflows
• Strong English communication skills for written feedback and team coordination
• Strong understanding of classical mechanics, electromagnetism, waves, optics, thermodynamics, statistical mechanics, quantum mechanics, relativity, units, dimensional analysis, and mathematical modeling
• Ability to check physics reasoning, formulas, dimensional analysis, and unit consistency
• Experience reviewing AI-generated or rubric-scored scientific work

Helpful Background

Experience with AI training, data annotation, LLM evaluation, scientific QA, academic review, or rubric-based review is a strong plus. The role also benefits from technical, documentation, and remote collaboration experience.

• Familiarity with Python, MATLAB, Mathematica, LaTeX, laboratory methods, data analysis, simulations, scientific visualization, and numerical methods
• Experience leading or supporting remote teams of educators, reviewers, researchers, annotators, science writers, or QAs
• Comfort using Discord, Google Sheets, Google Docs, trackers, dashboards, and project management systems
• Experience with physics research, teaching, tutoring, lab work, or scientific review

Work Details

This is a part-time, remote contractor opportunity for candidates located in the United States. The expected commitment is 20 or more hours per week, with compensation of up to $75 per hour.

• Employment type: Contractor
• Schedule: Part time, 20+ hours per week
• Location: Remote, United States
• Language: English
• Compensation: Up to $75 per hour