Applied Formal Methods Researcher (Lean 4) About the Role What if your deep mathematical training could directly shape how AI reasons about the hardest problems in mathematics?
Applied Physics Specialist
Remote (Global)
$40 – $80/hr
June 10, 2026
Job description
Applied Physics Specialist (AI Training)
About the Role
What if your years of graduate-level physics training could directly influence how AI reasons about the physical world? We're looking for PhD-level Applied Physicists to stress-test cutting-edge Large Language Models — exposing the gaps in their understanding of quantum mechanics, thermodynamics, electrodynamics, and more.
This is a fully remote, flexible contract role. No AI background needed — just deep domain expertise and the precision of a researcher who knows when something violates first principles.
- Organization: Alignerr
- Type: Hourly Contract
- Location: Remote
- Commitment: 10–40 hours/week
What You'll Do
- Design PhD-level problems — Craft advanced, open-ended physics problems requiring multi-step logical reasoning, mathematical derivation, and mastery of core physical principles
- Author ground-truth solutions — Write rigorous, step-by-step "golden responses" where every constant, unit conversion, and logical step is airtight
- Audit AI reasoning — Evaluate AI-generated solutions and proofs for physical consistency, identifying where models "hallucinate" physics that violates first principles
- Refine model behaviour — Provide structured, expert feedback that improves how AI handles boundary conditions, conservation laws, and physics-informed constraints
- Work independently and asynchronously — fully on your own schedule
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 ability to explain complex physical phenomena and mathematical derivations in clear, structured prose
- Uncompromising eye for detail — units, scientific notation, and the logical flow of a proof matter to you
- Self-motivated and consistent when working independently
- No prior AI or data annotation experience required
Nice to Have
- Experience with data annotation, scientific dataset evaluation, or academic benchmarking
- Proficiency with computational tools such as Python (NumPy/SciPy), MATLAB, or COMSOL
- Background in research, academia, or applied engineering environments
- Familiarity with AI tools or language model outputs as an end user
Why Join Us
- Work on high-impact AI projects alongside the world's leading AI research labs
- Fully remote and flexible — work when and where it suits you
- Freelance autonomy with the structure of meaningful, intellectually rigorous work
- Gain direct exposure to how frontier AI models are trained and evaluated
- Contribute to ensuring that the next generation of AI systems genuinely understands the physical world
- Potential for ongoing work and contract extension as new projects launch
Apply now
You will be redirected to the company's website to complete your application.
Researcher – Lean 4 & Formal Proof Systems (AI Training) About the Role What if your deep mathematical training could directly shape how AI understands and reasons through the hardest proofs in existence?
Formal Verification Scientist (Lean 4 & Mathlib) About the Role What if your deep mathematical training could directly shape how AI reasons about proofs — and push the boundaries of what machines can verify?
Lean 4 Proof Engineer — Mathematical Formalization (AI Training) About the Role What if your deep mathematical training could directly shape how AI reasons about formal proofs — and help push the boundaries of what machines can verify?