Applied Physics

Job summary

Develop advanced physics problems and precise, step-by-step reference solutions, then assess AI-generated simulations, proofs, and derivations for physical accuracy. Provide structured expert feedback to improve AI reasoning across core physics topics, working independently and asynchronously.

Job details

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 ensure they respect the fundamental laws of the universe. This is a fully remote, flexible contract role. No prior AI experience required — just deep mastery of physics and a sharp, rigorous mind. Organization: Alignerr Type: Hourly Contract Location: Remote Commitment: 10–40 hours/week What You'll Do Design advanced, open-ended physics problems at the level of PhD qualifying exams — requiring multi-step logical reasoning and rigorous mathematical derivation Author gold-standard solutions with precise, step-by-step workings, ensuring every physical constant, unit conversion, and boundary condition is flawless Evaluate AI-generated simulations, proofs, and derivations for physical consistency — identifying where models "hallucinate" physics that violates first principles Provide structured, expert feedback that helps AI develop sound physics-informed reasoning across topics like conservation laws, field theory, and statistical mechanics Work independently and asynchronously — fully on your own schedule Who You Are Holds a PhD (completed or near completion) in Applied Physics, Physics, Engineering Physics, or a closely related field Deep command of the core pillars of physics: Classical Mechanics, Electrodynamics, Statistical Mechanics, and Quantum Mechanics Exceptional ability to communicate complex physical phenomena and mathematical derivations in clear, structured English Uncompromising attention to detail — you catch unit errors, sign mistakes, and logical gaps without breaking a sweat Self-motivated and reliable when working independently No prior AI or tech experience required Nice to Have Experience with data annotation, scientific dataset evaluation, or quality assurance workflows Proficiency with tools such as MATLAB, COMSOL, or Python (NumPy / SciPy) Background in research-level benchmarking or technical writing 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 stimulating work Gain direct exposure to how frontier LLMs are trained and evaluated at the cutting edge Potential for ongoing work and contract extension as new projects launch

What you’ll do

Develop advanced physics problems and precise, step-by-step reference solutions, then assess AI-generated simulations, proofs, and derivations for physical accuracy. Provide structured expert feedback to improve AI reasoning across core physics topics, working independently and asynchronously.

Requirements

A completed or nearly completed PhD in Applied Physics, Physics, Engineering Physics, or a closely related field is required, along with deep knowledge of classical mechanics, electrodynamics, statistical mechanics, and quantum mechanics. Candidates should communicate complex concepts and derivations clearly in English, demonstrate exceptional attention to detail, and work reliably and independently; prior AI experience is not required.

Benefits

• Fully Remote Work
• Flexible Schedule
• Freelance Autonomy
• Intellectually Stimulating Work
• Exposure to Frontier AI Training and Evaluation
• Potential for Ongoing Work and Contract Extension

Listed skills

• Quality assurance · Preferred
• Attention to detail · Preferred
• Python · Preferred

Other relevant skills

Identified from the job description. Confirm important requirements above.

• Applied Physics
• Classical Mechanics
• Electrodynamics
• Statistical Mechanics
• Quantum Mechanics
• Mathematical Derivation
• Physical Reasoning
• Scientific Evaluation
• Technical Writing
• Attention to Detail
• Data Annotation
• Quality Assurance
• MATLAB
• COMSOL
• Python
• NumPy and SciPy

Job areas

• Science & Research
• Education
• Technology
• Data & Analytics

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