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About the role
Key responsibilities & impact- Develop and evaluate high-difficulty physics prompts spanning classical mechanics, quantum mechanics, electromagnetism, thermodynamics, and related areas
- Use adversarial prompting techniques to expose errors in model reasoning and problem-solving
- Provide expert critique of AI-generated responses, assessing both correctness and depth
- Work closely with project leads to uphold quality benchmarks
Requirements
What you’ll need- PhD in Physics or a closely related field
- Graduate-level expertise across multiple areas of physics
- Permanently based in the US
- Prior hands-on experience in AI data annotation or RLHF
- Excellent written communication and analytical skills
- Publications in peer-reviewed chemistry or physics journals.
- Experience with adversarial prompting, model evaluation, or AI red teaming strongly preferred
- Teaching, tutoring, or curriculum development experience in physical chemistry or theoretical sciences.
- Experience with computational chemistry tools (e.g., Gaussian, ORCA, MATLAB).
- Background in scientific annotation or technical quality assurance.
Benefits
Comp & perks- Flexible hours — contribute as much or as little as you’d like each week. (No minimum hours per week, capped at 40hrs/week.)
ATS Keywords
✓ Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills & Tools
adversarial promptingmodel evaluationAI red teamingcomputational chemistryphysical chemistrytheoretical sciencesdata annotationRLHFclassical mechanicsquantum mechanics
Soft Skills
written communicationanalytical skills
Certifications
PhD in Physics