Electrical Engineering — AI Data Trainer About the Role We partner with the world's leading AI research labs to build smarter, more technically capable AI models — and we need electrical engineers to make it happen.
Applied Physics
Job description
Applied Physics — AI Data Trainer
About the Role
What if your deep expertise in physics 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 reasoning and helping ensure they never violate the fundamental laws that govern reality.
This is a fully remote, flexible contract role built for researchers and scientists who want to do meaningful, intellectually rigorous 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
What You'll Do
- Design advanced physics problems — craft open-ended, multi-step challenges at PhD qualifying exam level, spanning quantum mechanics, electrodynamics, thermodynamics, and classical mechanics
- Author rigorous ground-truth solutions — produce step-by-step "golden responses" with exacting precision across every constant, unit, and derivation
- Audit AI-generated physics — evaluate model outputs for physical consistency, identifying where AI "hallucinates" results that violate first principles
- Refine model reasoning — provide structured, expert feedback that helps AI systems better handle boundary conditions, conservation laws, and physics-informed constraints
- Work independently and asynchronously — fully on your own schedule
Who You Are
- Holds a PhD (completed or in final stages) 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 analytical writing skills — you can explain complex derivations clearly and precisely in structured English
- Uncompromising attention to detail when it comes to units, scientific notation, and logical proof structure
- Self-motivated and reliable when working independently
- No prior AI or data annotation experience required
Nice to Have
- Prior experience with data annotation, dataset evaluation, or scientific quality assurance
- Proficiency with computational tools such as Python (NumPy/SciPy), MATLAB, or COMSOL
- Background in research-level benchmarking or academic problem design
- Familiarity with AI or LLM evaluation workflows
Why Join Us
- Work on cutting-edge AI projects alongside leading AI research labs
- Fully remote and flexible — work when and where it suits you
- Freelance autonomy with the structure of meaningful, high-impact work
- Apply your physics expertise to one of the most consequential challenges in modern AI
- Potential for ongoing work and contract extension as new projects launch
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