Experimental Materials Scientist for AI Modeling

Mercor; New York (NY); Remote; USD 110,000 - 170,000; Full time

Job summary

Mercor is seeking experimental scientists and engineers to support a frontier AI research lab focused on materials science. This is hands-on, expert-level work applying deep specialized knowledge to generate, structure, and evaluate scientific data that trains models.

Role involves designing experiments, reviewing AI outputs, and delivering model-ready datasets with strict timelines. Engagement is remote (US-based) with up to 40 hours per week, offering a unique opportunity to advance materials

Qualifications

• Hands-on experimental work across inorganic synthesis, superconductors, or semiconductors.
• Proficient materials characterization techniques (XRD, SEM, TEM, spectroscopy, electrical/transport measurements).
• Experience with thin-film growth or device fabrication (MBE/epitaxy, MOCVD, CVD, sputtering, clean-room).

Responsibilities

• Contribute domain expertise across synthesis, characterization, fabrication, and device physics to build high-quality training and evaluation data.
• Review and evaluate AI-generated scientific reasoning, catching errors and improving technical accuracy.
• Design and solve challenging, expert-level problems in your area of specialization.
• Rate and rank model outputs against defined scientific criteria, with clear written reasoning.
• Structure technical knowledge — experimental procedures, characterization results, process data — into well-organized, model-ready data.
• Deliver reliable, high-quality work within defined timelines.

Skills

Inorganic synthesis

Superconductors

Semiconductors

Thin-film growth

Device fabrication

Materials characterization

Education

PhD or MS in materials science/chemistry/physics or related field

Job description

Mercor is seeking experimental scientists and engineers to support a frontier AI research lab focused on materials science. This is hands-on, expert-level work applying deep specialized knowledge to generate, structure, and evaluate scientific data that trains models.

Role involves designing experiments, reviewing AI outputs, and delivering model-ready datasets with strict timelines. Engagement is remote (US-based) with up to 40 hours per week, offering a unique opportunity to advance materials