Applied Physics Specialist
About this role
About the Role What if your years of graduate-level physics training could directly influence how AI reasons about the physical world? We're looking for PhD-level Applied Physicists to stress-test cutting-edge Large Language Models — exposing the gaps in their understanding of quantum mechanics, thermodynamics, electrodynamics, and more. This is a fully remote, flexible contract role. No AI background needed — just deep domain expertise and the precision of a researcher who knows when something violates first principles. - Organization: Alignerr - Type: Hourly Contract - Location: Remote - Commitment: 10–40 hours/week What You'll Do - Design PhD-level problems — Craft advanced, open-ended physics problems requiring multi-step logical reasoning, mathematical derivation, and mastery of core physical principles - Author ground-truth solutions — Write rigorous, step-by-step "golden responses" where every constant, unit conversion, and logical step is airtight - Audit AI reasoning — Evaluate AI-generated solutions and proofs for physical consistency, identifying where models "hallucinate" physics that violates first principles - Refine model behaviour — Provide structured, expert feedback that improves how AI handles boundary conditions, conservation laws, and physics-informed constraints - Work independently and asynchronously — fully on your own schedule Who You Are - PhD completed or in final stages in Applied Physics, Physics, Engineering Physics, or a closely related field - Deep mastery of the core pillars: Classical Mechanics, Electrodynamics, Statistical Mechanics, and Quantum Mechanics - Exceptional ability to explain complex physical phenomena and mathematical derivations in clear, structured prose - Uncompromising eye for detail — units, scientific notation, and the logical flow of a proof matter to you - Self-motivated and consistent when working independently - No prior AI or data annotation experience required Nice to Have - Experience with data annotation, scientific dataset evaluation, or academic benchmarking - Proficiency with computational tools such as Python (NumPy/SciPy), MATLAB, or COMSOL - Background in research, academia, or applied engineering environments - Familiarity with AI tools or language model outputs as an end user Why Join Us - Work on high-impact AI projects alongside the world's leading AI research labs - Fully remote and flexible — work when and where it suits you - Freelance autonomy with the structure of meaningful, intellectually rigorous work - Gain direct exposure to how frontier AI models are trained and evaluated - Contribute to ensuring that the next generation of AI systems genuinely understands the physical world - Potential for ongoing work and contract extension as new projects launch
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