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Materials Science Domain Expert

AI expert network · Hybrid · Bay Area, CA · 40 hrs/week

Pay
$70–110/hr
Where
Hybrid · Bay Area, CA
Degree
See who gets hired
Posted
48d ago
Slots left
10
Checked
today

An older role: first posted 48d ago, and AI expert network still listed it when we checked today. Newer roles tend to fill faster. See the jobs hiring now.

What the work is

Join a leading AI lab's cutting-edge GenAI team to be at the core of the AI revolution, where your expertise fuels the development of the most advanced AI models.

Overview

We are hiring a senior materials science domain expert to work directly with a leading AI lab's research and program management teams, improving how frontier AI models reason about real materials science and materials engineering work.

Your materials expertise is the substance of this role. You will review the quality of materials knowledge work tasks, write the instruction specs and golden solutions that define what "correct" looks like, and build the benchmarks that show whether the model is genuinely improving. We are looking for a practicing specialist rather than a generalist.

Location: This is a hybrid role based in the Bay Area, California. You must live in the Bay Area and work on-site with the client's team multiple days each week, when required. This is not a remote role. If you do not currently live in the Bay Area, you must be willing to relocate there at your own cost before the engagement starts. Relocation assistance is not provided.

Key Responsibilities

  • Data QA and reviews: Vet the quality of materials science knowledge work tasks and model outputs, spotting missing behaviors, thin reasoning, unsupported structure to property claims, and answers that read well but would not survive technical scrutiny.
  • Instruction specs and golden datasets: Write high-quality instruction specs, produce golden solutions to materials problems, and define new materials tasks that reflect how the work is actually done in practice.
  • Benchmarks and domain depth: Design challenging materials science tasks and evaluation sets, and help build materials-specific skills and tools together with the research team.
  • Calibration: Work with client researchers and specialists in adjacent fields to keep standards consistent, translating tacit materials judgment into explicit, teachable criteria.

Who gets hired

  • Education: PhD in materials science, materials engineering, or a closely related discipline such as chemistry, chemical engineering, applied physics, or metallurgy. A master's degree with exceptional industrial depth may be considered.
  • Experience: 4+ years of substantive research or industrial R&D experience in materials, at a research university, a national laboratory, or an industrial research organization. Graduate coursework alone does not count.
  • Domain depth: Genuine specialization in at least one area, for example energy storage and battery materials, semiconductors and electronic materials, polymers and soft matter, structural alloys and metallurgy, characterization and microscopy, or computational materials and simulation.
  • Seniority: Clear progression to a senior level, for example Senior Scientist, Staff Scientist, Research Lead, Principal Investigator, or a senior industrial R&D role, with real ownership of research direction.
  • Research record: Peer-reviewed publications, granted patents, or shipped materials programs. Strongly preferred.
  • AI fluency: Hands-on working use of large language models in your professional work, and the judgment to tell a well-reasoned answer from a plausible-sounding wrong one.
  • Availability: Able to commit reliably to 40 hours per week for an initial engagement of 6 months.
  • Location: Living in the Bay Area, California, and able to work on-site with the client's team multiple days each week, when required. Candidates not currently based in the Bay Area must be willing to relocate there at their own cost. Relocation assistance is not provided.
  • Excellent written communication, and the ability to give precise, well-structured written feedback.

Pay

$70–110/hr, hybrid.

Apply now$70–110/hr