Materials Science Expert for AI‑Driven Engineering
Overview
A remote contractor role for a Materials Science Expert focused on advancing AI-assisted materials engineering. You’ll apply deep domain knowledge to help train next‑gen AI systems, guiding models on materials selection, failure analysis, testing, and process development. Expect to review AI-generated technical work for accuracy and deliver clear, practical feedback to support model learning. Strong communication and precise technical reasoning are essential as you collaborate with a distributed team.
What You'll Do7
- 1Assess complex materials science problems across selection, failure analysis, testing, and process development to guide AI input.
- 2Evaluate AI-generated technical responses for correctness and engineering quality and provide concrete feedback.
- 3Apply practical engineering judgment to real‑world material scenarios and theoretical queries.
- 4Analyze material issues using microstructural analysis, fractography, mechanical testing (tensile, fatigue, hardness), and thermodynamic/kinetic modeling to troubleshoot.
- 5Contribute domain expertise to improve AI reasoning and model performance in materials science tasks.
- 6Document findings and deliver clear written and verbal explanations to support AI learning and performance.
- 7Collaborate remotely with a distributed team of experts and project participants
Requirements7
- 1Bachelor’s degree or higher in Materials Science & Engineering, Metallurgy, or ME/ChemE with a materials focus.
- 2At least three years of hands‑on experience in materials selection, failure analysis, testing, or process development.
- 3Strong knowledge of metals, polymers, ceramics, and composites, including microstructure‑property relationships and common degradation modes.
- 4Proven ability to determine root causes from fractography, metallography, and mechanical/thermal data.
- 5Familiarity with ASTM, ASM, ISO standards and process qualification requirements.
- 6Excellent written and verbal communication in professional English.
- 7Experience with materials characterization tools (SEM, XRD, TEM, DSC/TGA) or manufacturing process development is a plus
Who Should Apply
The ideal candidate has solid, hands‑on experience in materials selection, failure analysis, and testing, and can translate technical insight into AI training inputs. This role suits professionals who enjoy precise, detail‑driven work and can articulate complex concepts clearly. It is less suitable for someone seeking a traditional lab bench position or full‑time on‑site work. Common fit concerns include limited experience with standardization bodies or insufficient track record in root‑cause analysis, and candidates who lack strong written English communication may score lower on collaboration and documentation needs.
Salary Insight
Compensation is task‑based and paid per completed item that meets project criteria; no fixed salary is provided here. Pay varies with task complexity and per‑submission requirements. Pay details are discussed later in the process.
Location
Required Skills
Application Tip
Highlight a specific project where you led a root‑cause analysis or authored a technical solution manual, and quantify its impact to demonstrate readiness for AI‑assisted materials work.
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How your application is processed
1Application received
Your resume and details are logged the moment you apply.
2ATS + eligibility screening
We check your profile against the role’s skills, seniority, and requirements.
3Employer sees qualified profiles only
Only candidates who clear screening move forward.
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