About the Role
What if your mastery of 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 where they break the laws of physics and helping ensure they reason with the rigour of a trained scientist.
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 deep domain expertise and an uncompromising eye for physical truth.
- Organization: Alignerr
- Type: Hourly Contract
- Location: Remote
- Commitment: 10–40 hours/week
What You'll Do
- Design Advanced Physics Problems — Craft challenging, open-ended problems at PhD qualifying exam level that demand multi-step logical reasoning, mathematical derivation, and mastery of core physical principles
- Author Rigorous Solutions — Produce definitive, step-by-step "golden responses" with perfect physical constants, unit conversions, and airtight logical flow
- Audit AI Reasoning — Evaluate AI-generated simulations, proofs, and explanations for physical consistency; identify where models "hallucinate" physics that violates first principles
- Refine Model Behaviour — Provide structured, expert feedback that teaches AI to respect constraints like conservation laws, boundary conditions, and dimensional analysis
- Cover Foundational Topics — Work across classical mechanics, electrodynamics, statistical mechanics, quantum mechanics, and related research-level domains
Who You Are
- Holds a PhD (completed or near completion) in Applied Physics, Physics, Engineering Physics, or a closely related field
- Deep mastery of the core pillars: Classical Mechanics, Electrodynamics, Statistical Mechanics, and Quantum Mechanics
- Exceptional ability to articulate complex physical phenomena and mathematical derivations in clear, structured English
- Uncompromising precision with units, scientific notation, dimensional analysis, and logical proof structure
- Self-motivated and reliable when working independently 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 research outputs
- Proficiency with computational tools such as Python (NumPy/SciPy), MATLAB, or COMSOL
- Background in research-level problem design, academic instruction, or scientific writing
- Familiarity with AI language models or large-scale model evaluation as an end user
Why Join Us
- Work on high-impact AI projects in collaboration with world-leading 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
- Contribute directly to ensuring AI systems reason about the physical world with scientific integrity
- Potential for ongoing work and contract extension as new projects launch