Materials Science AI Evaluation Expert

You will help improve AI systems by reviewing materials science content and writing accurate reference material. Your work will cover metals, ceramics, polymers, composites, phase diagrams, heat treatment, mechanical testing, corrosion, nanomaterials, and characterization.

• Create prompts and gold-standard materials science answers.
• Evaluate and rank AI-generated answers.
• Write precise feedback, technically accurate rewrites, and model answers.
• Check scientific accuracy, engineering reasoning, terminology, clarity, physical plausibility, and unit consistency.
• Review microstructure-property relationships and interpretations of experiments.
• Identify hallucinated properties, flawed processing advice, incorrect diagrams, unsafe design assumptions, unsupported performance claims, and overconfident interpretations.
• Fact-check technical claims and apply detailed review guidelines consistently across repeated tasks.

This is remote, part-time contract work for an experienced materials science professional. The role requires reliable, self-directed collaboration across time zones.

• $30 to $95 per hour.
• 20+ hours per week.
• Open to candidates in Australia, Austria, Belgium, Canada, Denmark, Finland, France, Germany, Gibraltar, Greece, Iceland, Ireland, Italy, Liechtenstein, Luxembourg, Malta, Monaco, New Zealand, Norway, Portugal, San Marino, Spain, Sweden, Switzerland, the United Kingdom, the United States, and the Netherlands.
• A bachelor's degree or higher in materials science, materials engineering, mechanical engineering, chemical engineering, metallurgy, polymer science, nanotechnology, or a related field, or equivalent professional experience.
• At least three years of relevant experience in research, engineering, laboratory work, manufacturing, teaching, technical writing, academic review, or related scientific or engineering work.
• Deep knowledge of structure-property relationships, crystal structures, phase diagrams, mechanical behavior, heat treatment, polymers, ceramics, metals, composites, corrosion, and characterization techniques.
• Strong professional English, careful attention to detail, sound technical judgment, and the ability to follow detailed guidelines consistently.
• Experience with AI training, scientific quality assurance, engineering quality assurance, technical content review, or rubric-based evaluation is preferred.

AI training is the human work behind better AI systems, including writing examples, reviewing model answers, and giving clear feedback. Materials science experts are needed to judge whether technical answers are accurate, practical, and scientifically sound.