Applied Physics

Applied Physics (AI Training)
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 the reasoning of cutting-edge Large Language Models — exposing where they break the laws of physics and helping build AI that actually gets the universe right.
This is a fully remote, flexible contract role built for researchers and domain experts. No prior AI experience needed — just deep command of physics 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 open-ended, multi-step problems at PhD qualifying exam level, spanning quantum mechanics, electromagnetism, classical mechanics, and thermodynamics
Author Gold-Standard Solutions — Write rigorous, step-by-step solutions with airtight derivations, correct physical constants, and perfect unit conversions
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 that helps AI systems reason correctly about boundary conditions, conservation laws, and physical constraints
Document Failure Modes — Systematically record how and where AI reasoning breaks down so research teams can address core weaknesses
Who You Are
PhD completed or in final stages 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 prose
Uncompromising attention to detail — units, notation, and logical flow matter to you
Self-directed and consistent 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 quality assurance workflows
Proficiency with MATLAB, COMSOL, Python (NumPy/SciPy), or similar scientific computing tools
Background in research-level benchmarking or academic problem-setting
Familiarity with AI tools or language model evaluation as an end user
Why Join Us
Work on high-impact AI projects alongside world-leading research labs
Fully remote and flexible — structure your work around your schedule
Freelance autonomy with the substance of meaningful, intellectually demanding work
Direct exposure to how frontier AI models are trained and evaluated
Contribute to ensuring AI respects the fundamental laws of the physical world
Potential for ongoing work and contract extension as new projects launch

Work arrangement
Yes