We are sharing a specialised consulting opportunity for experienced Materials Scientists and Engineers with strong expertise in materials selection, failure analysis, materials 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. The work requires strong hands-on technical experience, analytical judgement, and the ability to communicate complex scientific concepts clearly. No prior experience in AI is required.
Key Responsibilities
Materials Selection & Engineering Analysis
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Evaluate advanced materials-selection problems
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Compare metals, polymers, ceramics, composites, and related material systems
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Assess trade-offs involving mechanical, thermal, chemical, and processing requirements
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Apply practical engineering judgement to material-selection decisions
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Identify risks associated with inappropriate material choices
Failure Analysis
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Analyse real-world material failures
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Identify probable degradation or failure mechanisms
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Perform root-cause reasoning using available evidence
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Distinguish design, material, process, and service-related contributors
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Recommend technically defensible corrective actions
Microstructural Analysis
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Interpret microstructural features relevant to material performance
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Evaluate relationships between processing, structure, and properties
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Assess metallographic and related characterisation evidence
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Identify microstructural indicators associated with damage or failure
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Connect observed structure with expected engineering behaviour
Fractography & Root-Cause Investigation
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Review fracture surfaces and associated evidence
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Differentiate potential brittle, ductile, fatigue, or environmentally assisted failure mechanisms
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Evaluate whether observed damage supports proposed failure hypotheses
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Integrate fractographic findings with mechanical and process history
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Provide structured technical conclusions
Mechanical & Thermal Testing
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Analyse tensile, fatigue, hardness, and related mechanical-test results
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Evaluate thermal data where relevant
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Assess whether test methods and conclusions are technically appropriate
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Identify anomalous or inconsistent results
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Relate measured properties to design and service requirements
Materials Characterisation
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Interpret data from characterisation techniques such as SEM, XRD, TEM, DSC, and TGA where relevant
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Evaluate whether selected techniques are appropriate for the question being investigated
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Cross-check characterisation findings against proposed material behaviour
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Identify limitations or uncertainty in experimental interpretations
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Support technically sound conclusions based on available evidence
Thermodynamic & Kinetic Analysis
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Apply thermodynamic and kinetic reasoning to materials problems
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Evaluate phase stability and transformation behaviour
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Analyse processing-related effects on structure and performance
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Review modelling assumptions for scientific validity
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Connect theoretical predictions with practical materials behaviour
Process Development & Qualification
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Evaluate materials-related process-development scenarios
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Review process variables affecting final material performance
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Assess qualification requirements and process consistency
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Identify risks associated with process changes
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Apply relevant industry standards where appropriate
AI Engineering Evaluation
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Review AI-generated materials-science and engineering responses
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Assess technical correctness, completeness, and scientific quality
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Identify weak reasoning, unsupported conclusions, or inaccurate interpretations
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Provide structured feedback to improve model performance
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Contribute high-quality materials expertise to AI evaluation workflows
Technical Documentation & Collaboration
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Document findings and technical reasoning clearly
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Provide precise written and verbal explanations
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Collaborate remotely with project leads and other domain experts
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Support development of scenario-based technical tasks and case studies
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Contribute to quality assurance across scientific deliverables
Ideal Profile
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Bachelor's degree or higher in Materials Science & Engineering, Metallurgy, or a related discipline
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Mechanical Engineering or Chemical Engineering backgrounds with a strong materials specialisation may also be relevant
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At least 3 years of hands-on experience in materials selection, failure analysis, testing, or process development
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Strong knowledge of metals, polymers, ceramics, and composites
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Deep understanding of microstructure–property relationships
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Experience analysing degradation and failure mechanisms
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Proven ability to conduct root-cause failure analysis
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Familiarity with fractography and metallography
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Strong experience interpreting mechanical and thermal test data
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Knowledge of ASTM, ASM, ISO, or comparable materials standards
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Familiarity with process qualification requirements
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Experience with SEM, XRD, TEM, DSC/TGA, or related characterisation equipment is advantageous
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Manufacturing or process-development experience is highly valuable
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Strong analytical and critical-thinking skills
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Professional English proficiency
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Exceptional written and verbal technical communication skills
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Experience with technical literature review and scientific data interpretation
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Evidence of rigorous problem-authoring or technical-review experience is highly valued, including standards-committee work, examination item writing, textbook authorship, competition leadership, technical awards, publications, fellowships, grants, or comparable achievements
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No prior AI-training or model-evaluation experience is required
Engagement Details
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Independent contractor engagement
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Fully remote
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Displayed compensation range: $80–$130/hour
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Actual compensation structure is output-based, with payment made per task that meets project specifications
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Task completion time may vary depending on individual experience and workflow
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Minimum weekly submission requirements apply; the source does not specify the exact number of required tasks
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Work will involve materials selection, failure analysis, characterisation, mechanical and thermal testing, process development, scenario evaluation, and AI-generated engineering-content review
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Strong hands-on materials-science and engineering judgement is central to this engagement
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Roles are typically filled within approximately 48 hours
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Selected experts are expected to begin initial tasks within approximately 24–48 hours after onboarding
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Project scope, workload, materials topics, and evaluation standards may evolve depending on project requirements
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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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