Applied Physics Specialist
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 put cutting-edge AI models through their paces — designing rigorous problems, exposing flawed reasoning, and helping ensure that large language models genuinely respect the fundamental laws of nature. This is a fully remote, flexible contract role built for serious physicists who want to apply their expertise beyond the lab or classroom. No prior AI experience required — your domain mastery is what matters. - 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 that require multi-step logical reasoning, mathematical derivation, and deep physical intuition - Author Gold-Standard Solutions — Write rigorous, step-by-step "golden responses" with airtight physical constants, unit conversions, and logically sound proofs - Audit AI Reasoning — Evaluate AI-generated solutions and simulations for physical consistency, identifying where models hallucinate physics that violates first principles - Refine Model Behavior — Provide structured, expert feedback to improve AI reasoning around boundary conditions, conservation laws, and physics-informed constraints - Push the Limits of LLMs — Work across domains including quantum mechanics, electrodynamics, thermodynamics, and classical mechanics to expose failure modes in AI understanding Who You Are - Hold a PhD (completed or near-final stage) in Applied Physics, Physics, Engineering Physics, or a closely related field - Deep mastery across the core pillars of physics: Classical Mechanics, Electrodynamics, Statistical Mechanics, and Quantum Mechanics - Exceptionally strong analytical writing skills — you can explain complex derivations and physical phenomena in clear, structured prose - Uncompromising precision with units, scientific notation, and the logical flow of a rigorous proof - Self-motivated and consistent when working independently on task-based projects - No prior AI or machine learning experience required Nice to Have - Experience with data annotation, scientific dataset evaluation, or academic benchmark design - Proficiency with tools such as Python (NumPy/SciPy), MATLAB, or COMSOL - Background in research, academic publishing, or physics education Why Join Us - Work on genuinely cutting-edge AI projects alongside world-leading research labs - Fully remote and asynchronous — work on your own schedule, from anywhere - Freelance autonomy with the substance of high-impact, intellectually demanding work - Rare opportunity to see inside how frontier AI models are trained and evaluated - Potential for ongoing work and contract extension as new projects launch
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