Applied Physics
About this role
About the Role What if your deep expertise in physics could directly shape how AI understands the physical world? We're looking for PhD-level Applied Physicists to challenge cutting-edge Large Language Models on their grasp of fundamental physics — from quantum mechanics and electrodynamics to thermodynamics and classical mechanics. This is a fully remote, flexible contract role. No prior AI experience needed — just rigorous domain knowledge, precise analytical thinking, and the ability to spot when a model gets the physics wrong. - Organization: Alignerr - Type: Hourly Contract - Location: Remote - Commitment: 10–40 hours/week What You'll Do - Design Advanced Problem Sets — Craft university- and research-level physics problems requiring multi-step logical reasoning, mathematical derivation, and deep conceptual understanding — think PhD qualifying exam difficulty - Author Gold-Standard Solutions — Write rigorous, step-by-step solutions that serve as ground-truth references, with exacting precision on physical constants, units, and logical flow - Audit AI Reasoning — Evaluate AI-generated proofs and simulations for physical consistency, identifying where models "hallucinate" results that violate first principles - Refine Model Behaviour — Provide structured, expert feedback that helps AI systems develop physics-informed reasoning — correctly applying constraints like conservation laws, boundary conditions, and symmetry arguments - Document Failure Modes — Systematically record how and where AI reasoning breaks down, contributing directly to safer and more accurate AI outputs Who You Are - PhD completed or in final stages in Applied Physics, Physics, Engineering Physics, or a closely related discipline - Deep mastery across core physics pillars: Classical Mechanics, Electrodynamics, Statistical Mechanics, and Quantum Mechanics - Exceptional ability to communicate complex physical phenomena and mathematical derivations in clear, structured English - Uncompromising attention to detail — units, notation, and the logical integrity of a derivation all matter to you - Self-motivated and comfortable working independently in an asynchronous environment - No prior AI or data annotation experience required Nice to Have - Experience with scientific data annotation, evaluation systems, or data quality workflows - Proficiency with computational tools such as Python (NumPy/SciPy), MATLAB, or COMSOL - Background in research-level problem design or academic assessment - Familiarity with AI tools or large language models as an end user Why Join Us - Work on high-impact AI projects in collaboration with leading research labs and AI teams - Fully remote and flexible — structure your hours around your life - Freelance autonomy with meaningful, intellectually stimulating work - Gain firsthand exposure to how frontier AI models are trained and evaluated - Potential for ongoing work and contract extension as new projects launch
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