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  "job_description": "Applied Physics - AI Data Trainer\n• Location: Remote\n\nAbout The Job\n\nAt Alignerr, we partner with the world’s leading AI research teams and labs to build and train cutting-edge AI models.\n\nWe are seeking PhD-level Applied Physicists to challenge Large Language Models on their understanding of the physical world. You will work on university-level and research-level benchmarks in topics like quantum mechanics, electromagnetism, and thermodynamics. Your goal is to document failure modes in AI reasoning so we can ensure models respect the fundamental laws of the universe, such as conservation of energy and momentum. Work on high-impact projects while earning $40+/hour, fully remote, with flexible weekly hours.\n\nOrganization: Alignerr Position: Applied Physics - AI Data Trainer Type: Hourly Contract Compensation: $40–$80 /hour Location: Remote Commitment: 10–40 hours/week\n\nWhat You’ll Do\n• Develop Complex Problems: Design advanced, open-ended physics problems (equivalent to PhD qualifying exams) that require multi-step logical reasoning and mathematical derivation.\n• Author Ground-Truth Solutions: Create \"golden responses\" that provide rigorous, step-by-step solutions, ensuring that every physical constant and unit conversion is perfect.\n• Technical Auditing: Evaluate AI-generated simulations and proofs for physical consistency. You will identify where a model \"hallucinates\" physics that violates first principles.\n• Refine Reasoning: Provide structured feedback to improve the model’s ability to perform \"Physics-Informed\" reasoning, helping it understand constraints like boundary conditions and conservation laws.\n\nRequirements\n• Advanced Degree: PhD (completed or in the final stages) in Applied Physics, Physics, or a closely related field (e.g., Engineering Physics).\n• Domain Expertise: Mastery of the core pillars of physics: Classical Mechanics, Electrodynamics, Statistical Mechanics, and Quantum Mechanics.\n• Analytical Writing: Exceptional ability to explain complex physical phenomena and mathematical derivations in clear, structured English.\n• Precision: An uncompromising eye for detail regarding units, scientific notation, and the logical flow of a proof.\n• No AI experience required\n\nPreferred\n• Prior experience with data annotation, data quality, or evaluation systems for scientific datasets\n• Experience with tools such as MATLAB, COMSOL, or Python (NumPy/SciPy)\n\nWhy Join Us\n• Competitive pay and flexible remote work.\n• Collaborate with a team working on cutting-edge AI projects.\n• Exposure to advanced LLMs and how they’re trained.\n• Freelance perks: autonomy, flexibility, and global collaboration.\n• Potential for contract extension.\n\nApplication Process (Takes 15-20 min)\n• Submit your resume\n• Complete a short screening\n• Project matching and onboarding\n\nPS: Our team reviews applications daily. Please complete your AI interview and application steps to be considered for this opportunity.",
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