About the Role
What if your years of physics expertise could directly shape how AI understands the fundamental laws of the universe? We're looking for PhD-level Applied Physicists to stress-test cutting-edge Large Language Models — exposing the gaps in their physical reasoning and helping ensure AI never violates conservation of energy, momentum, or any other first principle.
This is a fully remote, flexible contract role built for researchers and academics who want high-impact work on their own schedule. No prior AI experience required — just a deep mastery of physics and an uncompromising eye for scientific rigor.
- Organization: Alignerr
- Type: Hourly Contract
- Location: Remote
- Commitment: 10–40 hours/week
What You'll Do
- Design PhD-Level Problems — Develop complex, open-ended physics problems equivalent to qualifying exam difficulty, requiring multi-step logical reasoning and rigorous mathematical derivation
- Author Ground-Truth Solutions — Create definitive, step-by-step "golden responses" where every physical constant, unit conversion, and logical step is airtight
- Audit AI Reasoning — Evaluate AI-generated proofs, simulations, and explanations for physical consistency, identifying where models "hallucinate" physics that violates first principles
- Refine Model Behavior — Provide structured, expert feedback to improve the model's physics-informed reasoning across boundary conditions, conservation laws, and physical constraints
- Work Across Core Domains — Apply expertise in Classical Mechanics, Electrodynamics, Quantum Mechanics, Thermodynamics, and Statistical Mechanics
Who You Are
- Advanced Degree — PhD completed or in final stages in Applied Physics, Physics, Engineering Physics, or a closely related field
- Deep Domain Mastery — Strong command across the core pillars: Classical Mechanics, Electrodynamics, Statistical Mechanics, and Quantum Mechanics
- Analytical Communicator — Exceptional ability to explain complex physical phenomena and mathematical derivations in clear, structured written English
- Precision-Oriented — Uncompromising attention to detail regarding units, scientific notation, dimensional analysis, and logical proof structure
- Self-Directed — Comfortable working independently and asynchronously 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 technical content
- Proficiency with scientific computing tools such as Python (NumPy/SciPy), MATLAB, or COMSOL
- Background in research publishing, academic instruction, or technical writing
- Familiarity with AI tools or language model evaluation as an end user
Why Join Us
- Work on cutting-edge AI projects alongside world-leading research labs
- Fully remote and flexible — work when and where it suits you
- Freelance autonomy with the structure of meaningful, high-impact work
- Rare opportunity to see inside how frontier AI models are trained and evaluated
- Direct influence on whether the next generation of AI reasons correctly about the physical world
- Potential for ongoing work and contract extension as new projects launch