Materials Scientist for AI Model Training

This is a hands-on, expert-level experimental role applying deep domain knowledge in inorganic materials, semiconductors, and superconductors to generate, structure, and evaluate the scientific data used to train and evaluate advanced materials-science models. Your contributions will directly influence how models understand materials, devices, and experimental processes.

• Provide domain expertise across synthesis, characterization, fabrication, and device physics to create high-quality training and evaluation data.
• Review and evaluate AI-generated scientific reasoning, identify errors, and improve technical accuracy.
• Design and solve challenging, expert-level problems within your specialization.
• Rate and rank model outputs against defined scientific criteria, documenting clear written reasoning for assessments.
• Structure technical knowledge, including experimental procedures, characterization results, and process data, into organized, model-ready formats.
• Deliver reliable, high-quality work within agreed timelines.

• Hands-on experimental experience in one or more of the following: inorganic synthesis, including solid-state, solution, solvothermal, and sol-gel methods; superconducting materials; or semiconductors and advanced packaging.
• Strong materials or device characterization skills, for example XRD, SEM, TEM, spectroscopy, and electrical or transport measurements.
• Experience with thin-film growth or device fabrication is a plus, including MBE or epitaxy, MOCVD, CVD, sputtering, IBAD, etch, and clean-room microfabrication.
• Advanced degree such as PhD or MS, or equivalent hands-on experience in materials science, chemistry, physics, or a related engineering field.
• Clear written English and the ability to explain technical reasoning concisely.

• Engagement type: Long-term, ongoing engagement.
• Hours: Up to 40 hours per week, with a minimum commitment of 10 hours per week.
• Work arrangement: Remote, must be based in the United States.
• Employment basis: Hourly.

Hourly pay: $84 per hour.

• Candidates must be able to work remotely from within the United States.