About the Role
We are looking for someone with a strong background in physics to review and assess AI-generated responses related to physics concepts. The role involves using Python to test, analyze, and verify the correctness of outputs, ensuring they meet technical and educational standards.
Responsibilities
- Evaluate AI-generated explanations of physics problems for technical accuracy
- Use Python scripts to automate validation of numerical solutions and units
- Identify inconsistencies or errors in scientific reasoning within AI responses
- Provide structured feedback on response quality and clarity
- Test edge cases in physics simulations generated by AI models
- Verify dimensional consistency and correctness of formulas used
- Assess alignment of answers with standard undergraduate-level physics curriculum
- Flag ambiguous or misleading explanations for revision
- Collaborate with technical reviewers to refine evaluation criteria
- Document common error patterns in physics-related outputs
- Ensure responses follow logical problem-solving structure
- Review AI-generated derivations for mathematical rigor
- Check for proper application of physical laws and principles
- Validate correctness of sample calculations provided in responses
- Improve testing frameworks by suggesting new validation scenarios
- Report issues through structured ticketing system
- Participate in calibration sessions to align scoring with team standards
- Review updates to AI models for regression in physics performance
- Contribute to development of physics-specific evaluation rubrics
- Maintain confidentiality of project content and internal processes
Nice to Have
- Graduate coursework in physics or applied mathematics
- Experience developing educational content in STEM
- Prior work in quality assurance or technical review
- Familiarity with machine learning concepts
- Contributions to open-source scientific Python projects
- Teaching experience at high school or university level
- Published work in physics or engineering
- Experience with automated testing frameworks
- Background in computational physics
- Prior freelance or contract-based technical work
Compensation
Hourly rate based on experience
Work Arrangement
Remote
Team
Distributed team across multiple time zones
Project Duration
Initial contract is for 3 months with potential for extension based on performance and project needs
Time Commitment
10–15 hours per week, flexible scheduling within weekly deadlines
Tools You’ll Use
Python 3, Jupyter Notebooks, Google Sheets, GitHub, Slack, and internal QA platforms
Evaluation Focus
Correctness of physics principles applied, clarity of explanation, and logical consistency in problem-solving steps
Onboarding Process
One-week training period with sample evaluations and feedback loops to calibrate scoring
Not applicable
