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)
