About this role
In this hourly, remote contractor role, you will work as a Materials Science Expert (SME) to review AI-generated materials science content and/or create high-quality materials science reference content, evaluating scientific accuracy, engineering reasoning, terminology, and step-by-step explanations while providing precise written feedback. You will assess outputs for correctness, clarity, physical plausibility, unit consistency, microstructure-property reasoning, experimental context, and adherence to the prompt; identify errors in crystal structure, phase diagrams, mechanical properties, polymers, ceramics, metals, composites, nanomaterials, processing methods, and characterization; fact-check claims when needed; write high-quality rewrites and model answers that demonstrate best practices in materials science explanation; and rate and compare multiple AI responses based on correctness and overall quality.
This role is with SME Careers, a fast-growing AI Data Services company and subsidiary of SuperAnnotate, delivering training data for many of the world’s largest AI companies and foundation-model labs. Your materials science expertise directly helps improve the world’s premier AI models by making their materials, engineering, and applied-science outputs more accurate, practical, and clearly explained.
Requirements
- 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.
- Strong professional proficiency in English, minimum C1, to follow guidelines and provide detailed feedback in English.
- 3+ years of experience in materials science research, materials engineering, laboratory work, manufacturing, teaching, technical writing, academic review, or related scientific/engineering work.
- Deep understanding of structure-property relationships, crystal structures, phase diagrams, mechanical behavior, heat treatment, polymers, ceramics, metals, composites, corrosion, and characterization techniques.
- Ability to evaluate materials explanations, calculations, diagrams, experimental interpretations, and engineering recommendations for accuracy and clarity.
- Comfortable identifying hallucinated material properties, incorrect processing claims, flawed microstructure reasoning, unsafe engineering suggestions, or unsupported performance claims.
- High attention to detail when reviewing units, material terminology, test methods, process conditions, assumptions, and design tradeoffs.
- Reliable, self-directed, and able to deliver consistent quality in an hourly, remote contractor workflow across time zones.
- Prior experience with AI data training/annotation, scientific QA, engineering QA, academic QA, technical content review, or rubric-based evaluation is strongly preferred.
Responsibilities
- Develop AI Training Content: Create prompts and gold-standard materials science answers across topics such as metals, ceramics, polymers, composites, phase diagrams, heat treatment, mechanical testing, corrosion, nanomaterials, and characterization.
- Optimize AI Performance: Evaluate and rank AI outputs to improve scientific accuracy, engineering logic, terminology, structure-property reasoning, clarity, and relevance to the user’s prompt.
- Ensure Model Integrity: Detect misleading materials claims, hallucinated properties, flawed processing recommendations, incorrect diagrams, unsafe design assumptions, and overconfident interpretations; validate reliability across materials science use cases.
Skills
- Composites
- Phase Diagrams
- Ceramics
- AI Training
- Materials Engineering
- English
- Scientific Review
- Polymers
- Metallurgy
- Materials Science
Additional skills
- Materials Science
- Materials Engineering
- Metallurgy
- Polymer Science
- Ceramics
- Composite Materials
- Nanomaterials
- Structure-Property Relationships
- Crystallography
- Phase Diagrams
- Heat Treatment
- Mechanical Behavior of Materials
- Corrosion Engineering
- Failure Analysis
- Materials Characterization
- Scanning Electron Microscopy (SEM)
- Transmission Electron Microscopy (TEM)
- X-ray Diffraction (XRD)
- Atomic Force Microscopy (AFM)
- Differential Scanning Calorimetry (DSC)
- Thermogravimetric Analysis (TGA)
- Mechanical Testing
- Metallography
- Microstructure Analysis
- Finite Element Analysis (FEA)
- Materials Modeling
- CALPHAD
- Technical Writing
- Peer Review
- Quality Assurance (QA)
