Applied Physics

Applied Physics - AI Data Trainer

About the Role

What if your deep expertise in physics could directly shape how AI understands the physical world - ensuring it never violates conservation of energy, misapplies quantum mechanics, or hallucinates impossible thermodynamics?

We're looking for PhD-level Applied Physicists to stress-test and train cutting-edge Large Language Models on university and research-level physics. You'll design problems that expose the limits of AI reasoning, author rigorous solutions, and provide structured feedback that teaches models to think like a physicist.

This is a fully remote, flexible contract role. No prior AI or data annotation experience required - just a mastery of physics and an uncompromising eye for scientific rigour.

• 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, mathematical derivation, and deep conceptual understanding across subfields
• Author Gold-Standard Solutions
  - Write rigorous, step-by-step "golden responses" with perfect unit conversions, physical constants, and airtight logical flow
• Audit AI Reasoning
  - Evaluate AI-generated proofs and simulations for physical consistency, identifying where models "hallucinate" physics that violates first principles
• Refine Model Behaviour
  - Provide structured, expert feedback that improves AI reasoning around boundary conditions, conservation laws, and physics-informed constraints
• Work Independently
  - Complete task-based assignments on your own schedule, fully asynchronously

Who You Are

• Holds a PhD (completed or near completion) in Applied Physics, Physics, Engineering Physics, or a closely related field
• Deep mastery across the core pillars: Classical Mechanics, Electrodynamics, Statistical Mechanics, and Quantum Mechanics
• Exceptional ability to explain complex physical phenomena and mathematical derivations in clear, structured English
• Precision-focused - you notice when units are off, when a derivation skips a step, or when a physical argument breaks down
• Self-motivated and consistent when working independently
• No prior AI or machine learning experience required

Nice to Have

• Experience with scientific data annotation, data quality evaluation, or benchmark creation
• Proficiency with computational tools such as Python (NumPy/SciPy), MATLAB, or COMSOL
• Background spanning multiple physics subfields or interdisciplinary research areas
• Experience writing for technical audiences - papers, textbooks, or problem sets

Why Join Us

• Work on high-impact AI projects in collaboration with 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, technically challenging work
• Apply your expertise to problems that genuinely matter - helping AI reason correctly about the physical universe
• Potential for ongoing work and contract extension as new projects launch