Physics AI Trainer - Advanced Problem Designer (Remote)

Anyone AI; Madrid; Presencial; EUR 29.000 - 48.000; A tiempo parcial

Descripción de la vacante

Anyone AI is seeking experts in physics to design high-quality, deterministic problems for frontier AI training. You will craft problems with a single verifiable solution and develop accompanying complete solutions and explanations.

This contract role is remote and part-time, with 20–40 hours per week. Applicants should hold a Master’s or PhD in Physics, with strong Python skills and experience in modeling, simulation, and multi-step problem solving.

Formación

• Master's or PhD in Physics and strong research or industry experience.
• Strong Python skills and familiarity with scientific libraries.
• Modeling, simulation, numerical methods, and multi-step problem solving.
• Ability to design original, difficult problems reflecting real physics workflows.
• Excellent attention to detail and technical writing in English.

Responsabilidades

• Design advanced physics problems for AI training and evaluation.
• Create deterministic problems with exactly one correct answer.
• Write complete, verified solutions and document the reasoning process.
• Develop problems testing deep physical reasoning beyond memorization.
• Use Python to build simulations or computational workflows where relevant.
• Ensure outputs are precise, reproducible, and well-written in English.

Conocimientos

Python

Technical writing

Problem design

English writing

Educación

Master's degree in Physics

PhD in Physics

Herramientas

NumPy

SciPy

Descripción del empleo

Anyone AI is seeking experts in physics to design high-quality, deterministic problems for frontier AI training. You will craft problems with a single verifiable solution and develop accompanying complete solutions and explanations.

This contract role is remote and part-time, with 20–40 hours per week. Applicants should hold a Master’s or PhD in Physics, with strong Python skills and experience in modeling, simulation, and multi-step problem solving.