Applied Physics

Applied Physics — AI Data Trainer
About The Role
What if your expertise in quantum mechanics, thermodynamics, and electrodynamics 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 build AI that respects 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 a deep command of physics and an uncompromising eye for rigour.
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 the level of PhD qualifying exams, requiring multi-step logical reasoning and precise mathematical derivation
Author Ground-Truth Solutions — Produce rigorous, step-by-step "golden responses" where every physical constant, unit, and logical step is exactly right
Audit AI Reasoning — Evaluate AI-generated simulations, derivations, and proofs for physical consistency; identify where models hallucinate physics that violates first principles
Refine Model Behaviour — Provide structured, expert feedback that improves the model's ability to reason within constraints like conservation laws, boundary conditions, and symmetry principles
Cover Core Domains — Work across Classical Mechanics, Electrodynamics, Statistical Mechanics, Quantum Mechanics, and related research-level topics
Who You Are
Holds a PhD (completed or near completion) 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
Exceptional analytical writer — able to communicate complex derivations and physical phenomena in clear, structured English
Obsessively precise with units, scientific notation, dimensional analysis, and logical proof structure
Self-directed and reliable when working independently on technical tasks
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 MATLAB, COMSOL, Python (NumPy/SciPy), or similar computational tools
Background in research-level simulation, numerical methods, or experimental physics
Familiarity with AI tools or language model evaluation as an end user
Why Join Us
Work on cutting-edge AI projects alongside world-leading research labs
Fully remote and flexible — structure your hours around your existing commitments
Freelance autonomy with the satisfaction of meaningful, intellectually demanding work
Direct impact on how AI models reason about the physical world — at the frontier of AI development
Potential for ongoing work and contract extension as new projects launch

Work arrangement
Yes