About this role · Stem
About the Role What if your deep expertise in physics 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 AI models — exposing gaps in their physical reasoning and helping ensure they never violate the principles of conservation of energy, momentum, or anything else your training tells you is non-negotiable. This is a fully remote, flexible contract role built for researchers and scientists who want high-impact work on their own schedule. No prior AI experience required — just a command of physics that goes all the way down to first principles. - Organization: Alignerr - Type: Hourly Contract - Location: Remote - Commitment: 10–40 hours/week What You'll Do - Design Advanced Physics Problems — Craft open-ended, multi-step problems at PhD qualifying exam level, spanning quantum mechanics, electrodynamics, thermodynamics, and classical mechanics - Author Gold-Standard Solutions — Write rigorous, step-by-step "golden responses" with flawless handling of physical constants, unit conversions, and mathematical derivations - Audit AI Reasoning — Evaluate AI-generated proofs and simulations for physical consistency, identifying where models hallucinate results or violate first principles - Refine Model Behavior — Provide structured, expert feedback that improves how AI handles boundary conditions, conservation laws, and physics-informed constraints - Document Failure Modes — Systematically record where and how AI reasoning breaks down so research teams can address root causes Who You Are - Completed or nearly completed PhD 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 ability to explain complex physical phenomena and mathematical derivations in clear, structured English - Uncompromising precision with units, scientific notation, and the logical structure of proofs - Self-directed and reliable — comfortable working independently on technical tasks without hand-holding - No prior AI or machine learning experience required Nice to Have - Experience with data annotation, scientific dataset evaluation, or quality assurance workflows - Proficiency with tools like Python (NumPy/SciPy), MATLAB, or COMSOL - Background in research publication, technical writing, or academic instruction Why Join Us - Work on some of the most technically demanding AI projects in existence alongside world-leading research labs - Fully remote and asynchronous — work when and where it suits you - Freelance autonomy with the structure of meaningful, high-value technical work - Rare opportunity to apply your physics expertise beyond academia in a high-impact, forward-looking field - Potential for ongoing work and contract extension as new projects launch