Materials Science Domain Expert

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.

Pay

Firm hourly pay: $70-$110 per hour

Location

Bay Area, CA

Eligibility

Location-specific or hybrid

Qualification difficulty

Selective

What this role involves

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. 1. 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. This is a full-time W-2 employment position with Cincinnatus LLC, with the opportunity to be placed at a leading AI lab as part of their extended workforce.

You will be provisioned with client-issued accounts and equipment, and will work inside the client's own tools alongside their research teams. 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. 2.

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. 3. Core Qualifications 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.