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 - 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
- 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
- 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
- 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
- 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
Vacancy posted 5 days ago
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