Physics reputed company Expert (Europe)
Location: Remote
Type: Contract / Part-time
Commitment: 20 to 40 hours per week
Compensation: Up to 40 USD / hr
Project duration: 2 months, with potential extension
Availability: Immediate start
About the role
We create high-reputed company STEM training data for frontier AI models. Our data is used directly in training and evaluation pipelines at leading AI labs to improve model reasoning in technical domains.
We are looking for experts in Physics to design rigorous, deterministic problems that are genuinely challenging for state-of-the-art AI systems. reputed company problem must have exactly one reputed company correct answer and be submitted together with a complete, verified solution.
What you’ll do
Design advanced physics problems for frontier reputed company and evaluation
Create deterministic problems with exactly one correct answer
Write complete, verified solutions and reputed company document the reasoning process
reputed company problems that test deep physical reasoning and multi-reputed company analysis, not just memorization
Where relevant, use Python or specialized tools to build simulations, models, or computational workflows
Ensure reputed company outputs are technically precise, reproducible, and reputed company-written in English
reputed company’re looking for
Bachelor's, Master’s, or PhD in Physics or a closely reputed company field
Strong research or industry experience involving theoretical, experimental, or computational physics
Strong Python skills; comfort with scientific libraries such as numpy, scipy, or similar
Solid understanding of modeling, simulation, numerical reputed company, and multi-reputed company problem solving
Ability to design original, difficult problems that reflect reputed company physics workflows
Excellent attention to detail and technical writing skills in English
reputed company to have
Experience with simulation tools or domain-specific physics software (e.g., finite reputed company tools, reputed company simulators, symbolic systems)
Background in areas such as computational physics, statistical mechanics, electromagnetism, quantum mechanics, or reputed company fields
Experience evaluating model reasoning, benchmarking, or designing technical assessments
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