Remote | Materials Scientist / Engineer — $80–$130/hour

We are sharing a specialised consulting opportunity for experienced Materials Scientists and Engineers with strong expertise in materials selection, failure analysis, characterisation, mechanical testing, microstructure–property relationships, process development, and scientific quality assurance to contribute to an advanced AI training and materials-engineering evaluation project.

Selected professionals will solve and review advanced materials-science problems, assess AI-generated technical responses, analyse real-world failure and selection scenarios, and provide rigorous feedback grounded in professional materials-engineering practice. No prior experience in AI is required.

Key Responsibilities

Materials Selection & Failure Analysis

• Evaluate materials-selection problems across metals, polymers, ceramics, composites, and related systems
• Assess trade-offs involving mechanical, thermal, chemical, processing, and service requirements
• Analyse material failures and identify likely degradation or failure mechanisms
• Distinguish design, material, process, and service-related contributors
• Recommend technically defensible corrective actions

Characterisation & Testing

• Interpret microstructure, metallography, fractography, and related evidence
• Evaluate tensile, fatigue, hardness, thermal, and other mechanical-test results
• Interpret data from SEM, XRD, TEM, DSC, TGA, or comparable techniques where relevant
• Assess whether test methods and characterisation approaches are appropriate
• Connect processing, structure, properties, and observed engineering behaviour

Process, Thermodynamics & Engineering Review

• Apply thermodynamic and kinetic reasoning to phase stability, transformation, and processing problems
• Evaluate process-development, qualification, and manufacturing scenarios
• Identify risks associated with process changes or inconsistent material behaviour
• Apply ASTM, ASM, ISO, or comparable standards where appropriate
• Review modelling assumptions and technical conclusions for scientific validity

AI Evaluation & Technical Documentation

• Review AI-generated materials-science and engineering responses for technical accuracy
• Identify weak reasoning, unsupported conclusions, or incorrect interpretations
• Provide structured feedback supporting model improvement
• Develop or review scenario-based technical tasks and case studies
• Document findings and engineering reasoning clearly

Ideal Profile

• Bachelor's degree or higher in Materials Science & Engineering, Metallurgy, or a related discipline
• Mechanical or Chemical Engineering backgrounds with a strong materials specialisation may also be relevant
• At least 3 years of hands-on experience in materials selection, failure analysis, testing, or process development
• Strong knowledge of metals, polymers, ceramics, and composites
• Deep understanding of microstructure–property relationships and degradation mechanisms
• Proven root-cause failure-analysis experience
• Familiarity with fractography, metallography, and mechanical or thermal testing
• Knowledge of ASTM, ASM, ISO, or comparable materials standards
• Experience with SEM, XRD, TEM, DSC/TGA, manufacturing, or process qualification is advantageous
• Strong analytical, critical-thinking, and technical communication skills
• Evidence of rigorous technical review, publication, standards work, problem authoring, or comparable achievements is highly valued
• No prior AI-training or model-evaluation experience is required

Engagement Details

• Independent contractor engagement
• Fully remote
• Displayed compensation range: $80–$130/hour
• Actual compensation structure is output-based, with payment made per task that meets project specifications
• Task completion time may vary depending on experience and workflow
• Minimum weekly submission requirements apply; the source does not specify the exact number of required tasks
• Work will involve materials selection, failure analysis, characterisation, mechanical and thermal testing, process development, scenario evaluation, and AI-generated engineering-content review
• Roles are typically filled within approximately 48 hours
• Selected experts are expected to begin initial tasks within approximately 24–48 hours after onboarding
• Project scope, workload, materials topics, and evaluation standards may evolve depending on project requirements
• Work must be completed without using confidential or proprietary information belonging to any employer, client, manufacturer, research institution, laboratory, or other third party

About the Platform

This opportunity is available through 24-MAG LLC. We connect experienced professionals with remote consulting opportunities across technical, evaluation, and project-based workstreams.

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