About this role
Role Overview
Apply hands-on expertise in inorganic materials, superconductors, semiconductors, and advanced packaging to help develop high-quality scientific data for AI models focused on materials science and the physical sciences. Your work will shape how models reason about materials, devices, and experimental processes.
Key Responsibilities- Contribute expertise in synthesis, characterization, fabrication, and device physics to create training and evaluation data.
- Review AI-generated scientific reasoning, identify errors, and improve technical accuracy.
- Design and solve challenging problems within your area of specialization.
- Rate and rank model outputs against defined scientific criteria, documenting clear written rationale.
- Organize experimental procedures, characterization results, and process data into structured, model-ready formats.
- Deliver reliable, high-quality work within established timelines.
- Hands-on experimental experience in one or more of the following areas: inorganic synthesis, including solid-state, solution, solvothermal, or sol-gel methods; superconducting materials; or semiconductors and advanced packaging.
- Strong materials or device characterization skills, such as XRD, SEM, TEM, spectroscopy, or electrical and transport measurements.
- Advanced degree, PhD or MS, or equivalent hands-on experience in materials science, chemistry, physics, or a related engineering discipline.
- Clear written English and the ability to explain technical reasoning concisely.
- Experience with thin-film growth or device fabrication is a plus, including MBE or epitaxy, MOCVD, CVD, sputtering, IBAD, etching, or clean-room microfabrication.
- Remote, US-based hourly engagement.
- Long-term, ongoing work.
- Commitment ranges from a minimum of 10 hours to up to 40 hours per week.
$84 per hour.