About the Role
What if your years of physics training could directly influence how AI understands the physical world? We're looking for PhD-level Applied Physicists to stress-test cutting-edge AI models — designing rigorous problems, auditing AI reasoning, and ensuring these systems never violate the fundamental laws that govern reality.
This is a fully remote, flexible contract role built for researchers and scientists who want to contribute to something genuinely consequential. No prior AI experience needed — just deep mastery of physics and the ability to think critically about where AI reasoning breaks down.
- Organization: Alignerr
- Type: Hourly Contract
- Location: Remote
- Commitment: 10–40 hours/week
What You'll Do
- Design Advanced Problems: Craft PhD qualifying exam-level physics problems that demand multi-step logical reasoning, rigorous mathematical derivation, and mastery of physical principles across domains like quantum mechanics, electromagnetism, and thermodynamics
- Author Ground-Truth Solutions: Develop precise, step-by-step "golden responses" — where every physical constant, unit conversion, and logical step is airtight and correct
- Audit AI Reasoning: Evaluate AI-generated simulations, proofs, and explanations for physical consistency — identifying where models "hallucinate" physics that violates first principles like conservation of energy or momentum
- Refine Model Behaviour: Provide structured, expert feedback that helps AI systems develop genuine physics-informed reasoning, including correct handling of boundary conditions, symmetry constraints, and conservation laws
Who You Are
- PhD completed or in final stages in Applied Physics, Physics, Engineering Physics, or a closely related field
- Deep command of the core pillars: Classical Mechanics, Electrodynamics, Statistical Mechanics, and Quantum Mechanics
- Exceptional analytical writing ability — you can explain complex derivations in clear, structured English without sacrificing rigour
- Obsessively precise about units, scientific notation, dimensional analysis, and the logical flow of a proof
- Self-motivated and comfortable working independently on task-based assignments
- 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 Python (NumPy/SciPy), MATLAB, or COMSOL
- Background in research-level benchmarking or physics education
Why Join Us
- Work on high-impact AI projects alongside the world's leading AI research labs
- Fully remote and flexible — work on your own schedule, wherever you are
- Apply your deepest expertise to problems that actually matter for the future of AI
- Freelance autonomy with the satisfaction of meaningful, intellectually demanding work
- Exposure to frontier AI models and how they are trained and evaluated
- Potential for ongoing work and contract extension as new projects launch