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Alignerr

Physics Masters

About this role

About the Role We're looking for physics graduates and postgraduates to help train and evaluate cutting-edge AI models being developed by the world's leading AI research labs. Your deep understanding of physics will directly shape how AI reasons through complex scientific problems — making a real impact on the next generation of intelligent systems. This is a fully remote, flexible contract role. No AI experience required. - Organization: Alignerr - Type: Hourly Contract - Location: Remote - Commitment: 10–40 hours/week What You'll Do - Design rigorous, advanced physics problems spanning mechanics, electromagnetism, thermodynamics, quantum mechanics, and more - Develop clear, step-by-step solutions with well-structured logical reasoning - Evaluate AI-generated responses for scientific accuracy, depth, and quality of reasoning - Collaborate with researchers to build and refine benchmarks across undergraduate to Masters-level physics topics - Work independently and asynchronously on your own schedule Who You Are - Currently pursuing or holding a Masters degree in Physics, Applied Physics, or a closely related field - Strong problem-solving ability across advanced physics domains - Able to communicate complex scientific concepts clearly and precisely in writing - Detail-oriented and comfortable providing structured, critical feedback - No prior AI or data annotation experience required Nice to Have - Experience with data annotation, quality evaluation, or academic benchmarking - Familiarity with AI language models or machine learning concepts - Background in research, tutoring, or technical writing Why Join Us - Work directly with industry-leading large language models on scientifically meaningful tasks - Fully remote and flexible — set your own hours and work from anywhere - Freelance perks: high autonomy, variety, and international collaboration - Contribute to AI research that pushes the boundaries of scientific reasoning - Potential for ongoing work and contract renewals

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