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? We're looking for PhD-level Applied Physicists to stress-test cutting-edge Large Language Models — exposing the gaps in their reasoning and helping ensure they never violate the fundamental laws of the universe.

This is a fully remote, flexible contract role. No prior AI experience needed — just mastery of physics and a rigorous, analytical mind.

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

What You'll Do

• Design Advanced Problems: Develop complex, open-ended physics problems at PhD qualifying exam level — requiring multi-step reasoning, mathematical derivation, and deep conceptual understanding across quantum mechanics, electromagnetism, thermodynamics, and beyond
• Author Gold-Standard Solutions: Write rigorous, step-by-step "golden responses" that serve as the definitive benchmark — every unit, constant, and logical step accounted for
• Audit AI Reasoning: Evaluate AI-generated simulations, proofs, and explanations for physical consistency — identifying where models "hallucinate" physics that violates first principles
• Refine Model Behavior: Provide structured, expert feedback that trains models to reason correctly about boundary conditions, conservation laws, symmetry principles, and physical constraints
• Probe Failure Modes: Systematically document how and where AI reasoning breaks down when confronted with research-level physics challenges

Who You Are

• PhD completed or in final stages 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 analytical writing skills — you can explain a complex derivation with precision and clarity
• Uncompromising attention to detail: units, scientific notation, dimensional analysis, and logical proof structure are second nature to you
• Self-motivated and reliable when working independently on technical tasks
• No prior AI or data annotation experience required

Nice to Have

• Experience with data annotation, scientific dataset evaluation, or quality assurance workflows
• Proficiency with computational tools such as Python (NumPy/SciPy), MATLAB, or COMSOL
• Background in research involving simulation, modelling, or experimental physics
• Familiarity with AI tools or language model evaluation as an end user

Why Join Us

• Work on high-impact 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, intellectually stimulating work
• Directly influence how AI understands and reasons about the physical world
• Potential for ongoing work and contract extension as new projects launch