AI Trainer - Materials Science Specialists; Remote - Leeds
Listing for:
prolificacademicltd
Part Time, Remote/Work from Home
position
Listed on 2026-11-15
Job specializations:
-
Research/Development
Job Description & How to Apply Below
Role overview
Join an expert network as a part-time Materials Science specialist supporting AI research and development, working remotely from the Leeds area. The role involves auditing scientific papers and machine-generated graphical abstracts to help improve the accuracy of large language models. Participation is structured as an opt-in talent pool, so individual assignments are offered based on client demand and fit rather than guaranteed hours.
Responsibilities- Review materials science research papers alongside LLM-produced graphical abstracts and flag discrepancies between the two.
- Evaluate whether the generated visuals faithfully summarize the source paper's findings, methods, and conclusions.
- Provide structured feedback and corrections that can be used to refine model outputs.
- Complete focused, paid tasks that may require up to one hour of uninterrupted concentration.
- Contribute domain expertise to researchers building more reliable AI systems.
- Master's degree or higher in materials science or a closely related discipline.
- Demonstrated depth of knowledge in materials science research and publishing practices.
- Prior experience with fact-checking, peer review, or AI-evaluation work is helpful.
- A verifiable professional profile (such as a Linked In presence or academic record).
- Strong attention to detail and the ability to sustain concentration on complex technical content.
- Reliable high-speed internet connection and access to a personal computer.
- Familiarity with how scientific figures and abstracts are constructed and interpreted.
- Experience annotating datasets or working with research-platform tooling.
- Fully remote work with flexible scheduling.
- Typical engagement rate of $40+/hr, with task length varying but generally under one hour.
- Onboarding is streamlined once an assessment is passed.
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