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 fundamental laws of the universe? We're looking for PhD-level Applied Physicists to stress-test cutting-edge AI models - exposing gaps in their physical reasoning and helping ensure they never violate the principles of conservation of energy, momentum, or anything else your training tells you is non-negotiable. This is a fully remote, flexible contract role built for researchers and scientists who want high-impact work on their own schedule. No prior AI experience required - just a command of physics that goes all the way down to first principles.
- Organization
: Alignerr - Type
: Hourly Contract - Location
: Remote - Commitment
: 10-40 hours/week
- Design Advanced Physics Problems
- Craft open-ended, multi-step problems at PhD qualifying exam level, spanning quantum mechanics, electrodynamics, thermodynamics, and classical mechanics - Author Gold-Standard Solutions
- Write rigorous, step-by-step "golden responses" with flawless handling of physical constants, unit conversions, and mathematical derivations - Audit AI Reasoning
- Evaluate AI-generated proofs and simulations for physical consistency, identifying where models hallucinate results or violate first principles - Refine Model Behavior
- Provide structured, expert feedback that improves how AI handles boundary conditions, conservation laws, and physics-informed constraints - Document Failure Modes
- Systematically record where and how AI reasoning breaks down so research teams can address root causes
- Completed or nearly completed PhD 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
- Uncompromising precision with units, scientific notation, and the logical structure of proofs
- Self-directed and reliable - comfortable working independently on technical tasks without hand-holding
- No prior AI or machine learning experience required
- Experience with data annotation, scientific dataset evaluation, or quality assurance workflows
- Proficiency with tools like Python (NumPy/SciPy), MATLAB, or COMSOL
- Background in research publication, technical writing, or academic instruction
- Work on some of the most technically demanding AI projects in existence alongside world-leading research labs
- Fully remote and asynchronous - work when and where it suits you
- Freelance autonomy with the structure of meaningful, high-value technical work
- Rare opportunity to apply your physics expertise beyond academia in a high-impact, forward-looking field
- Potential for ongoing work and contract extension as new projects launch
Vacancy posted 2 days ago
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