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Physics AI Training Specialist (Remote, Germany)

anyone-aiGermanyNew
Remote Contract $0/hr - $40/hr

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Experience Level

Experience

Qualifications

QualificationsA Bachelor's, Master's, or PhD in Physics or a closely related discipline. Extensive research or industry experience in theoretical, experimental, or computational physics. Proficiency in Python, with familiarity in scientific libraries like NumPy and SciPy. A strong grasp of modeling, simulation, numerical methods, and multi-step problem solving. Capability to devise original, challenging problems that emulate real-world physics workflows. Exceptional attention to detail and technical writing proficiency in English.

About the job

anyone-ai develops STEM training data that supports the advancement of AI models at leading research labs. The team’s work centers on producing high-quality, technically rigorous datasets that help improve AI reasoning in complex scientific domains.

This remote position, based in Germany, focuses on designing and writing advanced physics problems for AI training and evaluation. Each problem must be deterministic, have a single correct answer, and include a full, validated solution. The role requires clear documentation of reasoning and technical accuracy throughout the process.

What you will do

  • Develop challenging physics problems that require deep conceptual understanding and multi-step analysis.
  • Ensure every problem has one verifiable correct answer and is suitable for advanced AI systems.
  • Write thorough solutions, documenting each step and validating the reasoning process.
  • Use Python or other specialized tools as needed to build simulations, models, or computational workflows.
  • Produce outputs that are reproducible, technically sound, and clearly written in English.

About anyone-ai

anyone-ai is at the forefront of creating high-quality STEM training data that empowers AI models to reach their full potential. We are committed to advancing AI technology by providing precise and effective training resources that enhance model performance in real-world applications.

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