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Applied Physics Specialist (AI Training) About The Role What if your years of physics expertise could directly shape how AI understands the fundamental laws of the universe? We're looking for PhD-level Applied Physicists to stress-test cutting-edge Large Language Models — exposing the gaps in their physical reasoning and helping ensure AI never violates conservation of energy, momentum, or any other first principle. This is a fully remote, flexible contract role built for researchers and academics who want high-impact work on their own schedule. No prior AI experience required — just a deep mastery of physics and an uncompromising eye for scientific rigor. Organization: Alignerr Type: Hourly Contract Location: Remote Commitment: 10–40 hours/week What You'll Do Design PhD-Level Problems — Develop complex, open-ended physics problems equivalent to qualifying exam difficulty, requiring multi-step logical reasoning and rigorous mathematical derivation Author Ground-Truth Solutions — Create definitive, step-by-step "golden responses" where every physical constant, unit conversion, and logical step is airtight Audit AI Reasoning — Evaluate AI-generated proofs, simulations, and explanations for physical consistency, identifying where models "hallucinate" physics that violates first principles Refine Model Behavior — Provide structured, expert feedback to improve the model's physics-informed reasoning across boundary conditions, conservation laws, and physical constraints Work Across Core Domains — Apply expertise in Classical Mechanics, Electrodynamics, Quantum Mechanics, Thermodynamics, and Statistical Mechanics Who You Are Advanced Degree — PhD completed or in final stages in Applied Physics, Physics, Engineering Physics, or a closely related field Deep Domain Mastery — Strong command across the core pillars: Classical Mechanics, Electrodynamics, Statistical Mechanics, and Quantum Mechanics Analytical Communicator — Exceptional ability to explain complex physical phenomena and mathematical derivations in clear, structured written English Precision-Oriented — Uncompromising attention to detail regarding units, scientific notation, dimensional analysis, and logical proof structure Self-Directed — Comfortable working independently and asynchronously on task-based assignments No prior AI or data annotation experience required Nice to Have Experience with data annotation, scientific dataset evaluation, or quality assurance for technical content Proficiency with scientific computing tools such as Python (NumPy/SciPy), MATLAB, or COMSOL Background in research publishing, academic instruction, or technical writing Familiarity with AI tools or language model evaluation as an end user Why Join Us Work on cutting-edge AI projects alongside world-leading research labs Fully remote and flexible — work when and where it suits you Freelance autonomy with the structure of meaningful, high-impact work Rare opportunity to see inside how frontier AI models are trained and evaluated Direct influence on whether the next generation of AI reasons correctly about the physical world Potential for ongoing work and contract extension as new projects launch