Materials Science Expert Technical Evaluation

OpenTrain AI, Inc.; United States; Remote; USD 117,000 - 255,000; Part time

Job summary

OpenTrain AI, Inc. is seeking a Materials Science Expert for a fully remote, part-time contractor role.

You will create and review challenging materials science problems used to train and evaluate AI systems, combining deep materials science knowledge with careful scientific judgment. Responsibilities include designing problems across metals, ceramics, polymers, composites, and related fields, providing clear solutions, and building robust grading criteria.

Qualifications

• Master's or PhD in materials science, metallurgy, ceramics, polymers, or closely related field.
• Professional fluency in English.
• Experience in industrial or national laboratory research.
• Deep technical expertise in at least one materials science subdomain.
• Publications or patents are helpful but not required.

Responsibilities

• Design difficult technical problems covering structure–property relationships and materials processing.
• Build realistic scenarios with constraints and data that require more than a textbook answer.
• Provide correct analysis with clear, verifiable reasoning.
• Create objective grading criteria so independent reviewers can agree on outcomes.
• Review others' problems for technical accuracy and proper methods.
• Identify problems that are ambiguous or hard to evaluate.

Skills

Materials science

English fluency

Analytical judgment

Research experience

Education

Master's or PhD in materials science or related field

Job description

Materials Science Expert Technical Evaluation

Create and review difficult materials science problems for AI training, with clear solutions and grading criteria. This fully remote contractor role pays $85 to $185 per hour and offers flexible part-time work.

Remote Hourly · $85–$185/hr

$85–$185/hr

Compensation

Contract, part-time

Engagement

Remote

Location

Oct 31, 2026

Posted

Open in 52 countries

• Argentina
• Austria
• Canada
• Chile
• Colombia
• Egypt
• France
• Germany
• Ghana
• Greece
• India
• Italy
• Japan
• Jordan
• Kyrgyzstan
• Lebanon
• Malaysia
• Mexico
• Morocco
• Netherlands
• Oman
• Pakistan
• Philippines
• Portugal
• Qatar
• South Africa
• Spain
• Sri Lanka
• Tunisia
• United Arab Emirates
• United Kingdom
• United States
• Vietnam

The work

You will create and assess challenging technical problems used to train and evaluate AI systems. Your work will combine deep materials science knowledge with careful scientific judgment.

Problems may cover metals and alloys, ceramics and glasses, polymers and composites, semiconductors, thin films, characterization, computational materials, mechanical behavior, corrosion, or additive manufacturing materials.

• Design difficult problems involving structure-property relationships, materials processing, characterization, failure analysis, and computational materials.
• Build realistic technical scenarios with constraints and supporting data that require more than a textbook answer.
• Provide the correct analysis and explain the reasoning clearly enough for another scientist to verify.
• Create objective grading criteria so independent expert reviewers can reach the same conclusion.
• Review other contributors' problems for technical accuracy, sound methods, and clear grading.
• Identify problems that are ambiguous or cannot be evaluated reliably.

What it pays and takes

This is a fully remote contractor opportunity with flexible part-time work designed to fit alongside your current role.

• $85 to $185 per hour.
• Open to candidates in the listed countries across the Americas, Europe, Africa, Asia, and the Middle East.
• Professional fluency in English.
• A master's degree or PhD in materials science, metallurgy, ceramics, polymer science, condensed matter physics, or a closely related field.
• Principal-, staff-, or fellow-level experience in industrial or national laboratory research, or a faculty appointment at a leading university.
• Deep technical expertise and hands-on ownership in at least one materials science subdomain.
• Strong engineering and scientific judgment when interpreting constraints and comparing possible solutions.
• Ability to explain why an answer is correct so another scientist can verify it independently.
• Publications, patents, or technical leadership experience are helpful.
• Experience with AI or large-language-model evaluation is helpful but not required.

About AI training work

AI training work is the human side of building artificial intelligence. Experts create examples, write solutions, and review model responses so AI systems can produce more accurate and useful results. People with deep technical experience are needed when the work requires sound judgment in a specialized field.

Requirements

• Experience: Entry level