Materials Scientist / Engineer

$80–130/hrrate as listed

micro1 is contracting materials scientists and engineers to annotate technical datasets, write case studies, and review scientific deliverables that train frontier AI models. Work is remote and output-based, with observed rates in the $80–130/hr range depending on task complexity and throughput.

Summary, eligibility guidance and screening preparation are prepared by Sidequest from the platform's posting. Check the source listing before applying.

What the work involves

You'll spend most of your time producing and critiquing technical content that models learn from. That means interpreting experimental data and figures from the literature, writing detailed commentary that explains why a microstructure, failure mode, or phase transformation behaves as it does, and constructing realistic scenarios drawn from metallurgy, polymers, ceramics, composites, or semiconductor materials. A meaningful share of the work is review: checking another contributor's reasoning for factual errors, unsupported inferences, or explanations that sound authoritative but don't hold up against the underlying physics.

Expect tasks framed around characterization and property–structure relationships — SEM/TEM imagery, XRD patterns, DSC/TGA traces, tensile and fatigue data, spectroscopy. Literature review tasks ask you to synthesize methodologies and open problems rather than summarize abstracts. No prior AI or ML experience is required; the platform is buying your judgment about what a correct materials answer looks like.

What the screening measures

Credential verification — MS or PhD in materials science, metallurgy, mechanical, or chemical engineering with a materials focus.
Depth under follow-up — an AI interviewer will pick one technique or system you claim and push two or three layers past the surface answer.
Evaluation judgment — whether you can distinguish a plausible-sounding wrong explanation from a correct one, and articulate the difference in writing.
Written clarity — samples of technical prose matter more than resume length.

Logistics

Fully remote and asynchronous, with no fixed hours. Compensation is per accepted task rather than hourly, so the effective rate depends on how quickly you work and how often submissions pass review; minimum weekly submission quotas apply. micro1 typically fills these roles within 48 hours and expects first tasks within a day or two of onboarding, so apply when you actually have capacity.

What they look for

materials science expertise
materials characterization
technical literature review
scientific data interpretation
clear written and verbal communication
remote collaboration
annotating technical datasets
scenario and case study development
quality assurance in scientific deliverables
analytical skills

Before you apply

Would you pass this screen?

Drawn from what this listing actually requires. Answered in your browser — nothing is sent to us, and we do not store your answers.

Do you hold an MS, PhD, or equivalent advanced degree in Materials Science & Engineering, Metallurgy, Mechanical Engineering, Chemical Engineering, or a closely related discipline with a materials focus?
Master's or Doctoral degree in materials-relevant field · required
Have you personally used or supervised hands-on work with at least two materials characterization techniques (such as microscopy, spectroscopy, or mechanical testing) in a research, academic, or professional setting?
Hands-on materials characterization experience · required
Do you have documented experience communicating complex technical concepts clearly in writing—such as research publications, technical reports, thesis chapters, or reviewed documentation?
Technical writing and communication track record · preferred
Have you conducted or contributed to technical literature reviews, research syntheses, or data curation projects in materials science or a related field?
Literature review or data synthesis experience · preferred
Do you have experience working remotely using shared digital tools (such as Google Workspace, Confluence, GitHub, or similar platforms) to coordinate technical work?
Remote work and digital collaboration tools · preferred

0 of 5 answered

Included with this listing

Interview prep — 11 questions

Matched to what this platform's screening actually measures. Answer each out loud in 60–90 seconds: claim → concrete example → implication.

What it tests: This tests whether you have hands-on experience with the characterization methods the role demands (microscopy, spectroscopy, mechanical testing), and whether you can articulate technical reasoning clearly enough to train an AI system.
A strong answer: Name a specific project with one or two named techniques (e.g., SEM, XRD, tensile testing), describe what the data showed and what it meant physically, and explain how you presented it to a non-specialist audience or written form.
Where people lose it: Listing techniques without explaining what you actually did with the data, or describing results in jargon without breaking down the underlying physical meaning—the role requires you to teach an AI, not impress a peer.