About the Role
What if your years of rigorous physics training could directly shape how AI reasons about the physical world? We're looking for PhD-level Applied Physicists to stress-test and improve cutting-edge Large Language Models — probing their understanding of quantum mechanics, electrodynamics, thermodynamics, and more.
This is a fully remote, flexible contract role built for researchers and academics who want to do intellectually meaningful work on their own schedule. No prior AI experience needed — your deep domain expertise is what matters.
- Organization: Alignerr
- Type: Hourly Contract
- Location: Remote
- Commitment: 10–40 hours/week
What You'll Do
- Design Advanced Problems: Craft PhD-level, open-ended physics problems that demand multi-step logical reasoning, rigorous mathematical derivation, and mastery of first principles
- Author Ground-Truth Solutions: Write precise, step-by-step "golden responses" — verifying every constant, unit conversion, and logical step along the way
- Audit AI Reasoning: Evaluate AI-generated proofs and simulations for physical consistency, identifying where models "hallucinate" physics that violates fundamental laws
- Refine Model Behaviour: Provide structured, expert feedback that improves AI reasoning around boundary conditions, conservation laws, and physics-informed constraints
- Push the Boundaries: Work on university-level and research-level benchmarks spanning quantum mechanics, classical mechanics, electromagnetism, statistical mechanics, and more
Who You Are
- PhD completed or in final stages in Applied Physics, Physics, Engineering Physics, or a closely related field
- Deep mastery of the core pillars: Classical Mechanics, Electrodynamics, Statistical Mechanics, and Quantum Mechanics
- Exceptional analytical writing ability — you can explain complex derivations and physical phenomena in clear, structured English
- Uncompromising precision when it comes to units, scientific notation, and the logical flow of a proof
- Self-motivated and consistent when working independently
- No prior AI or data annotation experience required
Nice to Have
- Experience with data annotation, data quality, or evaluation workflows for scientific datasets
- Proficiency with computational tools such as Python (NumPy/SciPy), MATLAB, or COMSOL
- Background in research publication, academic instruction, or technical writing
Why Join Us
- Work on high-impact AI projects alongside the world's leading AI research labs
- Fully remote and flexible — structure your work around your research, teaching, or personal schedule
- Freelance autonomy with meaningful, intellectually stimulating task-based work
- Gain direct exposure to how frontier LLMs are trained and evaluated
- Potential for ongoing work and contract extension as new projects launch