Job description
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 challenge cutting-edge Large Language Models on their grasp of fundamental physics --- from quantum mechanics and electrodynamics to thermodynamics and classical mechanics.
This is a fully remote, flexible contract role. No prior AI experience needed --- just rigorous domain knowledge, precise analytical thinking, and the ability to spot when a model gets the physics wrong.
- Organization: Alignerr
- Type: Hourly Contract
- Location: Remote
- Commitment: 10--40 hours/week
What You'll Do
- Design Advanced Problem Sets --- Craft university- and research-level physics problems requiring multi-step logical reasoning, mathematical derivation, and deep conceptual understanding --- think PhD qualifying exam difficulty
- Author Gold-Standard Solutions --- Write rigorous, step-by-step solutions that serve as ground-truth references, with exacting precision on physical constants, units, and logical flow
- Audit AI Reasoning --- Evaluate AI-generated proofs and simulations for physical consistency, identifying where models "hallucinate" results that violate first principles
- Refine Model Behaviour --- Provide structured, expert feedback that helps AI systems develop physics-informed reasoning --- correctly applying constraints like conservation laws, boundary conditions, and symmetry arguments
- Document Failure Modes --- Systematically record how and where AI reasoning breaks down, contributing directly to safer and more accurate AI outputs
Who You Are
- PhD completed or in final stages in Applied Physics, Physics, Engineering Physics, or a closely related discipline
- Deep mastery across core physics pillars: Classical Mechanics, Electrodynamics, Statistical Mechanics, and Quantum Mechanics
- Exceptional ability to communicate complex physical phenomena and mathematical derivations in clear, structured English
- Uncompromising attention to detail --- units, notation, and the logical integrity of a derivation all matter to you
- Self-motivated and comfortable working independently in an asynchronous environment
- No prior AI or data annotation experience required
Nice to Have
- Experience with scientific data annotation, evaluation systems, or data quality workflows
- Proficiency with computational tools such as Python (NumPy/SciPy), MATLAB, or COMSOL
- Background in research-level problem design or academic assessment
- Familiarity with AI tools or large language models as an end user
Why Join Us
- Work on high-impact AI projects in collaboration with leading research labs and AI teams
- Fully remote and flexible --- structure your hours around your life
- Freelance autonomy with meaningful, intellectually stimulating work
- Gain firsthand exposure to how frontier AI models are trained and evaluated
- Potential for ongoing work and contract extension as new projects launch