About this role · Stem
About the Role What if your expertise in quantum mechanics, electrodynamics, and thermodynamics could directly shape how AI understands the physical world? We're looking for PhD-level Applied Physicists to stress-test cutting-edge AI models — exposing the gaps in their physical reasoning and helping ensure they never violate the fundamental laws of the universe. This is a fully remote, flexible contract role built for researchers and academics who want to do meaningful, intellectually stimulating work on their own schedule. No prior AI experience required — just deep domain mastery and a rigorous, analytical mind. - Organization: Alignerr - Type: Hourly Contract - Location: Remote - Commitment: 10–40 hours/week What You'll Do - Design Advanced Physics Problems — Craft PhD qualifying exam-level problems spanning quantum mechanics, electrodynamics, classical mechanics, and thermodynamics that demand multi-step logical reasoning and mathematical derivation - Author Gold-Standard Solutions — Develop rigorous, step-by-step "golden responses" where every physical constant, unit conversion, and logical step is unimpeachable - Audit AI Reasoning — Evaluate AI-generated proofs and simulations for physical consistency, identifying where models "hallucinate" physics that violates first principles - Provide Structured Feedback — Coach AI systems to reason correctly about boundary conditions, conservation laws, and real-world physical constraints - Document Failure Modes — Systematically record how and where AI reasoning breaks down so that research teams can build better, more physically grounded models Who You Are - Holds a PhD (completed or near-completion) in Applied Physics, Physics, Engineering Physics, or a closely related field - Deep mastery across the core pillars: Classical Mechanics, Electrodynamics, Statistical Mechanics, and Quantum Mechanics - Exceptional analytical writing skills — you can explain a complex derivation in clear, structured prose without losing rigor - Uncompromising precision when it comes to units, scientific notation, dimensional analysis, and the logical flow of a proof - Self-motivated and reliable when working independently and asynchronously - No prior AI or data annotation experience required Nice to Have - Experience with data annotation, scientific dataset evaluation, or quality assurance for research outputs - Proficiency with computational tools such as MATLAB, COMSOL, Python (NumPy/SciPy), or similar - Background in experimental or computational physics research - Familiarity with AI or machine learning concepts as an end user or researcher Why Join Us - Work on high-impact AI projects in collaboration with the world's leading AI research labs - Fully remote and flexible — work when and where it suits you, on your own schedule - Freelance autonomy with the intellectual depth of meaningful, research-level work - Gain direct exposure to how frontier large language models are trained and evaluated - Contribute to AI development that could shape how technology understands the physical world for decades to come - Potential for ongoing work and contract extension as new projects launch