About the Role
What if your expertise in quantum mechanics, electrodynamics, and thermodynamics could directly shape how AI understands the physical world? We're looking for PhD-level Applied Physicists to stress-test cutting-edge AI models — exposing the gaps in their physical reasoning and helping ensure they never violate the fundamental laws of the universe.
This is a fully remote, flexible contract role built for researchers and academics who want to do meaningful, intellectually stimulating work on their own schedule. No prior AI experience required — just deep domain mastery and a rigorous, analytical mind.
- Organization: Alignerr
- Type: Hourly Contract
- Location: Remote
- Commitment: 10–40 hours/week
What You'll Do
- Design Advanced Physics Problems — Craft PhD qualifying exam-level problems spanning quantum mechanics, electrodynamics, classical mechanics, and thermodynamics that demand multi-step logical reasoning and mathematical derivation
- Author Gold-Standard Solutions — Develop rigorous, step-by-step "golden responses" where every physical constant, unit conversion, and logical step is unimpeachable
- Audit AI Reasoning — Evaluate AI-generated proofs and simulations for physical consistency, identifying where models "hallucinate" physics that violates first principles
- Provide Structured Feedback — Coach AI systems to reason correctly about boundary conditions, conservation laws, and real-world physical constraints
- Document Failure Modes — Systematically record how and where AI reasoning breaks down so that research teams can build better, more physically grounded models
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 analytical writing skills — you can explain a complex derivation in clear, structured prose without losing rigor
- Uncompromising precision when it comes to units, scientific notation, dimensional analysis, and the logical flow of a proof
- Self-motivated and reliable when working independently and asynchronously
- No prior AI or data annotation experience required
Nice to Have
- Experience with data annotation, scientific dataset evaluation, or quality assurance for research outputs
- Proficiency with computational tools such as MATLAB, COMSOL, Python (NumPy/SciPy), or similar
- Background in experimental or computational physics research
- Familiarity with AI or machine learning concepts as an end user or researcher
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, on your own schedule
- Freelance autonomy with the intellectual depth of meaningful, research-level work
- Gain direct exposure to how frontier large language models are trained and evaluated
- Contribute to AI development that could shape how technology understands the physical world for decades to come
- Potential for ongoing work and contract extension as new projects launch