Join OpenTrain as a remote Materials Science AI Training Expert to review technical documents, write clear explanations of advanced materials concepts, and evaluate AI-generated materials engineering content. Part-time contractor role, 20+ hours/week, paid $80–$100/hr (USD).
Generative AI & RLHF
100% Remote Hourly · $80–$100/hr
$80–$100/hr
Compensation
Worldwide
Eligibility
Entry
Experience
Jul 29, 2026
Posted
Open worldwide
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OpenTrain is the #1 platform for finding and building careers in AI training and data labeling. We help people discover specialized AI training projects, build a unified portfolio, and grow freelance careers teaching AI — all from a remote, flexible setup.
OpenTrain AI is hiring directly for this role. Working with OpenTrain means contributing to how real-world AI systems are taught and improved while developing a durable specialty in materials-science annotation and evaluation.
About AI training and why it matters
AI training (data labeling, annotation, and human feedback) is the human side of building intelligent systems. Materials-science expertise helps AI models generate accurate engineering guidance, interpret scientific literature, and reason about materials selection and processing.
This work is remote, flexible, and accessible: contributors shape state-of-the-art models by producing, reviewing, and validating high-quality domain examples and evaluations.
The role
As a Materials Science AI Training Expert you will review and annotate technical materials datasets and literature, create clear explanations of advanced concepts, and evaluate AI-generated materials engineering content for scientific accuracy and clarity.
You will also develop and validate domain-specific scenarios, case studies, and problem sets used to teach and test models, and help define data requirements and quality benchmarks for interdisciplinary projects.
Contractor, part-time role with a minimum commitment of 20+ hours per week.
Work is 100% remote and worldwide; English proficiency is required.
Labeling work focuses on documents and technical text (classification, NER, text generation, and evaluation rating).
What you'll do day-to-day
You will operate as a domain specialist reviewing technical content and shaping training data. Tasks are document-focused and blend annotation, writing, and evaluation.
Review and annotate materials-science literature, reports, and documentation for accuracy and clarity.
Write comprehensive explanations of advanced materials concepts for both expert and non-expert audiences.
Evaluate and provide structured feedback on AI-generated content related to materials engineering and metallurgy.
Develop and validate materials-focused scenarios, case studies, and problem sets for model training and evaluation.
Help define data requirements, labeling schemas, and quality benchmarks to meet project specifications.
Required qualifications
You must bring domain expertise and strong communication skills. These requirements are firm because the role demands rigorous scientific judgment applied to training data and model outputs.
MS or PhD in Materials Science & Engineering, Metallurgy, Mechanical Engineering, Chemical Engineering, or a closely related field with materials specialization.
Experience in materials characterization, processing, selection, or testing across applications.
Proven ability to read scientific literature and interpret experimental data accurately.
Clear written and verbal communication skills for explaining complex technical topics.
Experience evaluating or improving AI-generated technical content, or demonstrated ability to assess technical outputs against scientific standards.
Familiarity with remote collaboration tools and structured content review workflows.
Compensation, schedule, and logistics
This is a remote contractor position paid hourly in USD. Expect focused, document-centric labeling and review work with typical tasks that mix writing, classification, NER tagging, and evaluation ratings.
Hourly pay: $80–$100 USD per hour (PAY_PER_HOUR).
Time commitment: 20+ hours per week (part-time contractor).
Work style: remote and flexible; schedule coordination may be required for project milestones and reviews.
Data types: DOCUMENT. Labeling tasks include classification, entity/NER+classification, text generation, and evaluation rating.
Who should apply and how to apply
This opportunity is ideal for early-career through experienced materials scientists and engineers who want to apply their technical expertise to shape AI behavior. If you hold an MS or PhD and enjoy translating complex science into clear guidance, you’ll fit well.
To apply, create an OpenTrain account and submit your profile and application for this role. OpenTrain manages contracting, payments, and project coordination so you can focus on high-quality technical work.
Open to applicants worldwide who can work in English.
Entry-level experience designation refers to time in industry; advanced degree is required.
Applications should highlight relevant materials projects, publications, or examples of technical writing and data review.
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