Applied Physics - #227967

Applied Physics — AI Data Trainer

About The Role

What if your expertise in quantum mechanics, electrodynamics, and thermodynamics could directly shape how AI understands the physical world? 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 build AI that truly respects the fundamental laws of the universe.

This is a fully remote, flexible contract role designed for researchers and academics who want to apply their deep domain knowledge to one of the most consequential technology challenges of our time. No prior AI experience required.

• Organization: Alignerr
• Type: Hourly Contract
• Location: Remote
• Commitment: 10–40 hours/week
  
  

What You'll Do

• Design Advanced Physics Problems — Craft PhD-qualifying-exam-level problems requiring multi-step logical reasoning, mathematical derivation, and deep physical intuition across domains like quantum mechanics, electromagnetism, and thermodynamics
• Author Rigorous Solutions — Produce precise, step-by-step "golden responses" with flawless physical constants, unit conversions, and logical structure that serve as ground-truth benchmarks
• Audit AI Reasoning — Evaluate AI-generated simulations, proofs, and derivations for physical consistency; identify where models "hallucinate" physics that violates first principles
• Refine Model Behaviour — Provide structured, expert feedback that helps AI systems develop physics-informed reasoning — correctly applying boundary conditions, conservation laws, and symmetry constraints
  
  

Who You Are

• Hold a PhD (completed or near completion) in Applied Physics, Physics, Engineering Physics, or a closely related field
• Possess mastery across the core pillars: Classical Mechanics, Electrodynamics, Statistical Mechanics, and Quantum Mechanics
• Can explain complex physical phenomena and rigorous mathematical derivations in clear, well-structured English
• Obsessively precise — you notice a wrong unit, a sign error, or a broken logical step immediately
• Self-directed and comfortable working independently in an asynchronous environment
• No prior AI or machine learning experience required
  
  

Nice to Have

• Experience with data annotation, dataset quality review, or scientific evaluation frameworks
• Proficiency with computational tools such as Python (NumPy/SciPy), MATLAB, or COMSOL
• Background in research-level benchmarking or academic problem-set design
  
  

Why Join Us

• Work on frontier AI projects in partnership with the world's leading AI research labs
• Fully remote and flexible — structure your hours around your existing commitments
• Apply your expertise to problems that genuinely matter — shaping how AI reasons about physical reality
• Freelance autonomy: no bureaucracy, no commute, just meaningful, intellectually engaging work
• Potential for ongoing contract extension as new projects launch