About the Role
What if your deep expertise in physics could directly influence how AI reasons about the physical world? We're looking for PhD-level Applied Physicists to stress-test and improve the scientific reasoning of cutting-edge Large Language Models — exposing where they break the laws of thermodynamics, mishandle quantum mechanics, or hallucinate results that violate first principles.
This is a fully remote, flexible contract role built for working researchers and academics. No prior AI experience needed — just mastery of physics and a rigorous analytical mind.
- Organization: Alignerr
- Type: Hourly Contract
- Location: Remote
- Commitment: 10–40 hours/week
What You'll Do
- Design advanced physics problems — craft PhD qualifying exam-level challenges spanning quantum mechanics, electrodynamics, thermodynamics, and classical mechanics that require multi-step reasoning and mathematical derivation
- Author ground-truth solutions — produce rigorous, step-by-step "golden responses" with precise units, constants, and logical flow that set the standard for correct physical reasoning
- Audit AI-generated reasoning — evaluate AI outputs for physical consistency, identifying where models hallucinate results or violate fundamental principles like conservation of energy and momentum
- Refine model reasoning — deliver structured, expert feedback that helps AI systems better understand boundary conditions, physical constraints, and the deep logic of first-principles reasoning
- Document failure modes — systematically record where and how AI reasoning breaks down under rigorous scientific scrutiny
Who You Are
- PhD completed or in final stages in Applied Physics, Physics, Engineering Physics, or a closely related field
- Deep mastery across the core pillars: Classical Mechanics, Electrodynamics, Statistical Mechanics, and Quantum Mechanics
- Exceptional ability to write clear, structured explanations of complex physical phenomena and mathematical derivations
- Uncompromising attention to detail — units, scientific notation, dimensional analysis, and logical proof structure are second nature to you
- Self-motivated and able to work independently on complex, open-ended problems
- No prior AI or machine learning experience required
Nice to Have
- Experience with scientific data annotation, evaluation, or quality assurance
- Proficiency with MATLAB, COMSOL, Python (NumPy/SciPy), or similar computational tools
- Background in research publishing, academic benchmarking, or scientific peer review
- Familiarity with AI tools or language model evaluation as an end user
Why Join Us
- Work on genuinely high-impact AI projects in collaboration with leading research labs
- Fully remote and flexible — structure your hours around your existing research or academic commitments
- Freelance autonomy with meaningful, intellectually challenging work that uses your full expertise
- Contribute to ensuring that AI systems are grounded in real scientific truth
- Potential for ongoing work and contract extension as new projects launch