Materials Science Domain Expert | $70-$110/hr Remote
Overview
You will work directly with a leading AI lab's research and program management teams, applying your materials science expertise to improve how frontier models reason about real engineering work. Your main activities are validating materials knowledge tasks, writing instruction specs and golden solutions, and designing benchmarks that track model progress. Cincinnatus LLC employs you full-time on a W-2 basis, and you will operate inside the client's own tools with client-issued equipment. The role demands a PhD-level specialist with 4+ years of research or industrial R&D experience. The position is hybrid and based in the Bay Area, so you must live locally and be available on-site several days per week.
What You'll Do4
- 1Review materials science tasks and model outputs to catch shallow reasoning, unsupported structure-property claims, and answers that sound credible but fail technical scrutiny.
- 2Author instruction specifications and golden solution sets that define correct answers for model training and evaluation.
- 3Create new materials problems and evaluation benchmarks that reflect real-world materials engineering practices.
- 4Collaborate with client researchers and adjacent-field experts to align grading standards and convert implicit materials judgment into explicit scoring criteria.
Requirements9
- 1Hold a PhD in materials science, materials engineering, or a closely related field like chemistry, chemical engineering, applied physics, or metallurgy. A master's degree with exceptional industrial depth may be accepted.
- 2Bring 4+ years of hands-on research or industrial R&D experience at a university, national lab, or industrial research organization. Graduate coursework alone will not count.
- 3Show deep specialization in at least one materials area, such as batteries and energy storage, semiconductors, polymers and soft matter, structural alloys, characterization and microscopy, or computational materials science.
- 4Demonstrate senior-level career progression, for example Senior Scientist, Staff Scientist, Research Lead, Principal Investigator, or an equivalent industrial R&D role, with real ownership of research direction.
- 5Provide evidence of impact through peer-reviewed publications, granted patents, or shipped materials programs.
- 6Use large language models hands-on in your daily professional work and be able to distinguish well-reasoned technical answers from plausible-sounding errors.
- 7Commit to a full-time schedule of 40 hours per week for an initial 6-month engagement.
- 8Live in the Bay Area or be willing to relocate at your own expense, and be available to work on-site with the client team multiple days per week when requested.
- 9Write clear, structured, and precise feedback that research teams can act on.
Who Should Apply
The ideal candidate is a practicing materials scientist with a PhD, 4+ years of hands-on R&D, and a proven track record of publications or patents in a specific domain like battery materials, semiconductors, or metallurgy. You should already use large language models as part of your daily workflow and feel confident judging whether a model's technical reasoning actually holds up. This role is less suitable for materials science educators or recent graduates whose experience is mostly coursework, or for researchers who prefer fully remote work and cannot commit to on-site presence in the Bay Area. Rejection often comes from a lack of deep specialization or from not showing clear ownership of research direction at a senior level. Another common miss is failing to demonstrate concrete, professional use of LLMs in the application.
Salary Insight
The pay range is $70-$110 per hour, and the spread reflects where you sit on the seniority spectrum. A master's-level scientist with strong industrial depth would likely land near the lower end, while a PhD with a publication record and senior-level ownership can expect the higher end. The role is full-time W-2, so benefits and payroll run through Cincinnatus LLC.
Location
Required Skills
Application Tip
When applying, include a short paragraph describing a specific incident where you used an LLM to analyze or critique a materials science problem, and explain how you determined the answer was correct or flawed. This directly demonstrates the AI fluency and technical judgment the role requires.
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