Physics QA / AI Trainer Job
We are seeking a highly skilled Physics QA / AI Trainer to join our team. As a Physics QA / AI Trainer, you will be responsible for reviewing physics prompts and model responses, verifying step-by-step reasoning, and authoring improved solutions and prompts that raise quality and rigor.
This is an exciting opportunity to contribute to the development of next-generation AI systems that can reason through university-level physics. You will work closely with leading AI companies to build safer, smarter systems that rely on expert-reviewed data and rigorous evaluation.
Job Responsibilities :
- Audit physics Q&A and model outputs for correctness, clarity, notation, and quantitative / experimental rigor across mechanics, electromagnetism, thermodynamics, quantum, and applied physics.
- Evaluate responses against detailed QA rubrics; assign ratings and write concise rationales.
- Draft improved prompts, gold-standard solutions, and constructive feedback (SFT / RLHF / evaluation).
- Run quick validation checks in Python (e.g., sanity checks, symbolic / numerical verification; NumPy / SymPy / Pandas helpful).
- Identify edge cases, propose rubric refinements, and help enforce consistent quality standards.
Requirements :
3+ years professional / academic experience in physics or a closely related domain (applied physics, engineering, scientific computing).Bachelor's in Physics or related field (Master's / PhD preferred).Practical Python skills for analysis / simulation / validation scripts.Ability to review multi-step derivations, equations, units, and assumptions across core topics.Strong written English; comfortable following detailed QA rubrics and writing clear, actionable feedback.Reliable computer / internet; responsive and detail-oriented.Nice to Have :
Teaching / lecturing, tutoring, or problem-set / rubric design experience.Prior LLM QA / RLHF / SFT or scientific content review experience.About Us :
We equip cutting-edge AI with expert-reviewed data and rigorous evaluation. Our goal is to build AI systems that can reason through complex physical concepts like university-level physics.