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 Large Language 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, high-impact work on their own schedule. No prior AI experience required — just deep domain mastery and an uncompromising eye for scientific rigor.
- Organization: Alignerr
- Type: Hourly Contract
- Location: Remote
- Commitment: 10–40 hours/week
What You'll Do
- Design Advanced Problems — Craft complex, open-ended physics problems at PhD qualifying exam level, requiring multi-step logical reasoning and rigorous mathematical derivation
- Author Ground-Truth Solutions — Produce precise, step-by-step "golden responses" where every physical constant, unit conversion, and logical step is airtight
- Audit AI Reasoning — Evaluate AI-generated proofs and simulations for physical consistency, identifying where models "hallucinate" physics that violates first principles
- Refine Model Behaviour — Provide structured, expert feedback to improve AI reasoning in areas like conservation laws, boundary conditions, and physics-informed constraints
- Work Across Core Domains — Engage with topics spanning Classical Mechanics, Electrodynamics, Statistical Mechanics, Quantum Mechanics, and beyond
Who You Are
- Holds a PhD (completed or in final stages) in Applied Physics, Physics, Engineering Physics, or a closely related field
- Deep mastery of the core pillars of physics — Classical Mechanics, Electrodynamics, Statistical Mechanics, and Quantum Mechanics
- Exceptional ability to communicate complex physical phenomena and mathematical derivations in clear, structured English
- Uncompromising precision with units, scientific notation, dimensional analysis, and the logical flow of a proof
- Self-motivated and reliable when working independently on task-based assignments
- No prior AI or machine learning experience required
Nice to Have
- Experience with data annotation, scientific dataset evaluation, or academic peer review
- Proficiency with tools such as Python (NumPy/SciPy), MATLAB, or COMSOL
- Background in research publication, 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 leading research labs
- Fully remote and flexible — work when and where it suits you
- Freelance autonomy with the structure of meaningful, intellectually engaging work
- Apply your expertise to problems that directly shape how AI understands the physical universe
- Potential for ongoing work and contract extension as new projects launch