Physics AI Problem Contributor
A Physics AI Problem Contributor helps train and evaluate AI by applying expert physics knowledge to structured data, model outputs and quality review workflows.
Create scientifically rigorous problems, demonstrations and explanations that help models learn physical reasoning rather than memorize answers.
Key responsibilities
- Author tasks in mechanics, E&M, thermodynamics, optics and modern physics.
- Supply assumptions, units and worked solutions.
- Create adversarial distractors and realistic boundary conditions.
- Rate difficulty and prerequisite knowledge.
What we look for
- Physics degree or engineering equivalent; teaching, research or technical writing experience valuable.
How success is measured
Scientific validity, task acceptance, difficulty calibration.
How this works on Jwuma
Candidate profile → skills evidence → domain assessment → calibration task → qualification → project matching → production → peer review → expert QA → performance feedback and progression. Corpshore AI service alignment Applicable across annotation and labeling, RLHF and preference data, model evaluation and red-teaming, multimodal datasets and specialized AI data operations, depending on project scope.
Common questions
What does a Physics AI Problem Contributor do?
A Physics AI Problem Contributor helps train and evaluate AI by applying expert physics knowledge to structured data, model outputs and quality review workflows.
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