Applied Physics — AI Data Trainer

About The Role

What if your expertise in quantum mechanics, electrodynamics, and thermodynamics could directly shape how AI understands the physical universe? We're looking for PhD-level Applied Physicists to stress-test cutting-edge Large Language Models — exposing the gaps, hallucinations, and reasoning failures that occur when AI tries to grapple with the fundamental laws of nature.

This is a fully remote, flexible contract role built for researchers and scientists who want to do meaningful, intellectually rigorous work on their own schedule. No prior AI experience required — your deep domain knowledge is what matters.

Organization: Alignerr

Type: Hourly Contract Location: Remote Commitment: 10–40 hours/week

What You'll Do

Design Advanced Physics Problems — Craft complex, open-ended problems at PhD qualifying exam level, requiring multi-step logical reasoning, mathematical derivation, and first-principles thinking across subfields like quantum mechanics, electrodynamics, statistical mechanics, and classical mechanics Author Rigorous Ground-Truth Solutions — Develop precise, step-by-step "golden responses" where every physical constant, unit conversion, and logical transition is held to the highest standard of scientific accuracy Audit AI Reasoning — Evaluate AI-generated simulations, proofs, and explanations for physical consistency; identify where models "hallucinate" physics that violates conservation laws, boundary conditions, or other fundamental principles Provide Structured Feedback — Document failure modes clearly and deliver actionable feedback that helps AI systems develop genuinely physics-informed reasoning Work Independently — Complete task-based assignments asynchronously, on a schedule that works for you

Who You Are

Holds a PhD (completed or near-final stage) in Applied Physics, Physics, Engineering Physics, or a closely related field Mastery across the core pillars: Classical Mechanics, Electrodynamics, Statistical Mechanics, and Quantum Mechanics Exceptional analytical writing ability — you can explain complex derivations and physical phenomena with clarity, precision, and structure Uncompromising attention to detail when it comes to units, scientific notation, mathematical logic, and physical consistency Self-directed and reliable when working independently No prior AI or data annotation experience required

Nice to Have

Experience with data annotation, scientific dataset evaluation, or quality review workflows Proficiency with computational tools such as Python (NumPy/SciPy), MATLAB, or COMSOL Background in research involving simulation, modeling, or experimental physics Familiarity with AI tools or language models as an end user

Why Join Us

Work on cutting-edge AI projects alongside leading AI research labs

Fully remote and flexible — work when and where it suits you Apply your PhD-level expertise to problems that genuinely challenge you intellectually Freelance autonomy with the structure of meaningful, high-impact work Gain rare, first-hand exposure to how frontier AI models are trained and evaluated Potential for ongoing work and contract extension as new projects launch