Physics Quality Assurance Lead Remote Contractor

About Open Train

Open Train is the #1 platform for finding and building careers in AI training and data labeling. Open Train AI is hiring and contracting for this role, helping contributors find meaningful work teaching and evaluating AI while building experience in a fast-growing field.

• Remote contractor opportunity
• Part-time schedule of 20+ hours per week
• U.S. hiring only
• Apply in minutes through Open Train

AI systems learn from examples that people prepare, review, and improve. In this role, your physics expertise will help evaluate model-generated explanations, calculations, diagrams, derivations, and scientific reasoning so that contributors can produce accurate, clear, rubric-aligned training data.

• Work directly on the human side of building modern AI
• Use subject-matter expertise to evaluate model outputs
• Help improve the accuracy and quality of physics-focused AI training

Open Train 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 provide precise written feedback that helps contributors meet project rubrics. The role also includes identifying recurring quality issues, communicating guideline updates, supporting onboarding, maintaining documentation, running training calls for physics contributors, and helping activate contributors who are not working consistently.

• Contractor role with up to $75 per hour
• Intermediate experience level
• English-language work
• 20+ hours per week

You will combine detailed physics review with quality operations and contributor support. Your feedback should make errors easy to understand and help trainers, QAs, and contributors consistently apply project-specific expectations.

• Review physics explanations, calculations, diagrams, derivations, experimental interpretations, and step-by-step reasoning.
• Evaluate work against project guidelines and project-specific rubrics.
• Flag incorrect assumptions, wrong formulas, unit errors, flawed reasoning, sign convention mistakes, physically impossible claims, and misleading explanations.
• 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 for physics contributors and help communicate guideline updates.

Applicants should have a strong quantitative academic or professional foundation and the ability to evaluate both the science and presentation of physics work. Clear English communication is essential for written feedback, documentation, and team coordination.

• Degree in Physics, Applied Physics, Engineering Physics, Astrophysics, Mathematics, Engineering, or a closely related quantitative field.
• Strong English communication skills for written feedback and team coordination.
• At least 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 check physics reasoning, formulas, dimensional analysis, and unit consistency.
• Experience reviewing AI-generated or rubric-scored scientific work.

The following experience is helpful for this role but is not listed as required. It can support both the technical review work and the coordination responsibilities involved in physics quality assurance.

• Experience with AI training, data annotation, LLM evaluation, scientific QA, academic review, or rubric-based review.
• 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 with Discord, Google Sheets, Google Docs, trackers, dashboards, and project management systems.

Physics quality assurance gives you a direct role in shaping how AI handles technical explanations and scientific reasoning. AI training and data-labeling work is a growing way to apply specialized knowledge remotely, with flexible project opportunities across the industry.

• Apply advanced physics knowledge to cutting-edge AI development
• Work remotely with a flexible part-time contractor arrangement
• Help contributors produce more reliable scientific training data
• Build experience in AI evaluation and quality assurance