Applied Physics
About this role
About the Role What if your deep expertise in physics could directly shape how AI understands the physical world — from quantum mechanics to thermodynamics to the fundamental laws that govern reality? We're looking for PhD-level Applied Physicists to stress-test cutting-edge AI models, expose their reasoning failures, and help train them to think like a physicist. Your work will directly influence how the next generation of AI handles real scientific problems — and whether it respects the laws of the universe when it does. This is a fully remote, flexible contract role. No prior AI experience required — just a mastery of physics and a sharp analytical mind. - 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 and rigorous mathematical derivation across areas like quantum mechanics, electrodynamics, and thermodynamics - Author gold-standard solutions — Write definitive, step-by-step solutions with exacting attention to physical constants, unit conversions, and logical flow - Audit AI reasoning — Evaluate AI-generated simulations, derivations, and proofs for physical consistency; identify where models "hallucinate" physics that violates first principles - Refine model behaviour — Provide structured, expert feedback that helps AI develop true physics-informed reasoning, including boundary conditions, symmetry constraints, and conservation laws Who You Are - Hold a PhD (completed or near-completion) in Applied Physics, Physics, Engineering Physics, or a closely related field - Have mastery across the core pillars: Classical Mechanics, Electrodynamics, Statistical Mechanics, and Quantum Mechanics - Write with exceptional clarity — able to explain complex physical phenomena and mathematical derivations in structured, precise English - Obsessively detail-oriented when it comes to units, scientific notation, and the logical integrity of a proof - Self-directed and comfortable working independently on technical tasks - No prior AI or data annotation experience required Nice to Have - Experience with scientific computing tools such as Python (NumPy/SciPy), MATLAB, or COMSOL - Prior work in data annotation, dataset curation, or scientific evaluation systems - Background in research involving simulation, modelling, or experimental physics Why Join Us - Work on high-impact AI projects in collaboration with world-leading research labs - Fully remote and asynchronous — work on your own schedule, wherever you are - Freelance autonomy with meaningful, intellectually stimulating work - Direct exposure to frontier AI development and how large language models are trained on scientific reasoning - Potential for ongoing work and contract extension as new projects launch
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