Applied Physics — AI Data Trainer
About The Role
What if your deep expertise in physics could directly shape how AI understands the physical world — ensuring it never violates conservation of energy, misapplies quantum mechanics, or hallucinates impossible thermodynamics?
We're looking for PhD-level Applied Physicists to stress-test and train cutting-edge Large Language Models on university and research-level physics. You'll design problems that expose the limits of AI reasoning, author rigorous solutions, and provide structured feedback that teaches models to think like a physicist.
This is a fully remote, flexible contract role. No prior AI or data annotation experience required — just a mastery of physics and an uncompromising eye for scientific rigour.
- Organization: Alignerr
- Type: Hourly Contract
- Location: Remote
- Commitment: 10–40 hours/week
What You'll Do
- Design Advanced Problems — Craft PhD qualifying exam-level physics problems that demand multi-step logical reasoning, mathematical derivation, and deep conceptual understanding across subfields
- Author Gold-Standard Solutions — Write rigorous, step-by-step "golden responses" with perfect unit conversions, physical constants, and airtight logical flow
- 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 improves AI reasoning around boundary conditions, conservation laws, and physics-informed constraints
- Work Independently — Complete task-based assignments on your own schedule, fully asynchronously
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: Classical Mechanics, Electrodynamics, Statistical Mechanics, and Quantum Mechanics
- Exceptional ability to explain complex physical phenomena and mathematical derivations in clear, structured English
- Precision-focused — you notice when units are off, when a derivation skips a step, or when a physical argument breaks down
- Self-motivated and consistent when working independently
- No prior AI or machine learning experience required
Nice to Have
- Experience with scientific data annotation, data quality evaluation, or benchmark creation
- Proficiency with computational tools such as Python (NumPy/SciPy), MATLAB, or COMSOL
- Background spanning multiple physics subfields or interdisciplinary research areas
- Experience writing for technical audiences — papers, textbooks, or problem sets
Why Join Us
- Work on high-impact AI projects in collaboration with the world's leading AI research labs
- Fully remote and flexible — work when and where it suits you
- Freelance autonomy with the structure of meaningful, technically challenging work
- Apply your expertise to problems that genuinely matter — helping AI reason correctly about the physical universe
- Potential for ongoing work and contract extension as new projects launch
