Applied Physics
Alignerr
Applied Physics - AI Data Trainer About the Role What if your deep expertise in physics could directly shape how AI understands the physical world - from quantum mechanics to thermodynamics to the fundamental laws that govern reality? We're looking for PhD-level Applied Physicists to stress-test cutting-edge AI models, expose their reasoning failures, and help train them to think like a physicist. Your work will directly influence how the next generation of AI handles real scientific problems - and whether it respects the laws of the universe when it does. This is a fully remote, flexible contract role. No prior AI experience required - just a mastery of physics and a sharp analytical mind.
- Organization
: Alignerr - Type
: Hourly Contract - Location
: Remote - Commitment
: 10-40 hours/week
- Design advanced physics problems
- Craft complex, open-ended problems at PhD qualifying exam level, requiring multi-step logical reasoning and rigorous mathematical derivation across areas like quantum mechanics, electrodynamics, and thermodynamics - Author gold-standard solutions
- Write definitive, step-by-step solutions with exacting attention to physical constants, unit conversions, and logical flow - 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 helps AI develop true physics-informed reasoning, including boundary conditions, symmetry constraints, and conservation laws
- Hold a PhD (completed or near-completion) in Applied Physics, Physics, Engineering Physics, or a closely related field
- Have mastery across the core pillars: Classical Mechanics, Electrodynamics, Statistical Mechanics, and Quantum Mechanics
- Write with exceptional clarity - able to explain complex physical phenomena and mathematical derivations in structured, precise English
- Obsessively detail-oriented when it comes to units, scientific notation, and the logical integrity of a proof
- Self-directed and comfortable working independently on technical tasks
- No prior AI or data annotation experience required
- Experience with scientific computing tools such as Python (NumPy/SciPy), MATLAB, or COMSOL
- Prior work in data annotation, dataset curation, or scientific evaluation systems
- Background in research involving simulation, modelling, or experimental physics
- Work on high-impact AI projects in collaboration with world-leading research labs
- Fully remote and asynchronous - work on your own schedule, wherever you are
- Freelance autonomy with meaningful, intellectually stimulating work
- Direct exposure to frontier AI development and how large language models are trained on scientific reasoning
- Potential for ongoing work and contract extension as new projects launch
Vacancy posted 2 days ago
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