Applied Physics Expert (AI Training)

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