Generate, structure and evaluate expert ALD and thin-film data for a frontier AI lab building semiconductor and physical-science models: solve hard problems, rate model reasoning, and turn recipes into model-ready data. US-based, 10–40 hours a week, $84/hour.
Build and evaluate training data for a frontier lab's materials science models: DFT, AIMD, classical MD, surface and adsorption modeling, reaction energetics. For US-based computational PhDs fluent in VASP, Quantum ESPRESSO, CP2K, LAMMPS or ASE. Long-term, 10–40 hours a week, $84/hour.
Author AI evaluation tasks from real fire and life safety review work: egress plan checks, sprinkler and alarm review, hazmat control areas, firestop photo verification. For US fire marshals, fire protection engineers and NICET III+ designer-reviewers with 3+ years in the seat. Remote hourly contract at $45–60/hour.
A full-time W-2 placement at a leading AI lab through Cincinnatus LLC: US-based mechanical engineers vet model outputs, write instruction specs and reference solutions, and build benchmarks. 5+ years in industry and a mechanical engineering degree required. 40 hours a week for an initial 2–3 months, $60–90/hour.
Experimental scientists create and review training data for a frontier lab's materials science models: inorganic synthesis, superconductors, semiconductors and advanced packaging, characterization (XRD, SEM, TEM) and fabrication. PhD, MS or equivalent hands-on experience. US-based, 10–40 hours a week, $84/hour.
Full-time Bay Area hybrid role embedded with an AI lab: review model reasoning on materials problems, write golden solutions and specs, and build benchmarks. For materials PhDs (or master's with exceptional industrial depth) with 4+ years of R&D. W-2 via Cincinnatus, $70–110/hour.
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