AI Trainer - Graphical Abstract - Physics (Remote - Toronto)

Role overview

This opportunity invites materials science specialists into an expert network that supplies high-quality human feedback to AI research projects. Participants review LLM-generated graphical abstracts alongside the papers they are meant to summarize, identifying errors that help retrain and improve model performance. Engagements are paid per task and depend on client demand and fit.

Responsibilities

- Compare LLM-generated graphical abstracts with the underlying materials science papers - Flag specific instances where visuals misrepresent methodology, results, or scope - Contribute structured feedback that shapes how the AI model summarizes future papers - Finish self-contained paid assignments, each requiring up to an hour of uninterrupted focus - Communicate findings in clear, actionable language suitable for engineering review

Requirements

- Deep expertise in materials science, graphical abstract design, or both - Verifiable professional profile or documented work history - Ability to sustain concentration on detailed analytical work for up to one hour - Reliable, fast internet connection and a working computer - A PayPal account to receive client payments

Nice to have

- Prior work in fact-checking, technical editing, or AI evaluation pipelines - Familiarity with peer review in scientific publishing

Benefits and work setup

- Typical researcher-side pay of $40+/hr for completed tasks - Fully remote, task-based commitments with flexible scheduling - Onboarding assessment before invitations to paid projects begin