Remote Materials Scientist: Semiconductors & Superconductors

Zekai; United States; Remote; USD 90,000 - 140,000; Part time

Job summary

Zekai seeks experimental scientists and engineers across inorganic synthesis, characterization, superconductors, and semiconductors to support a frontier AI research lab building models for materials science and the physical sciences. This is hands-on, expert-level work requiring deep, specialized knowledge to generate, structure, and evaluate scientific data for model learning.

Remote, US-based engagement up to 40 hours/week for a long-term contract.

Qualifications

• Hands-on experimental experience in inorganic synthesis (solid-state, solution, solvothermal, sol-gel) or related areas.
• Strong materials or device characterization skills (XRD, SEM, TEM, spectroscopy, electrical/transport measurements).
• Experience with thin-film growth or device fabrication (MBE/epitaxy, MOCVD, CVD, sputtering, clean-room) is a plus.
• Advanced degree (PhD/MS) in materials science, chemistry, physics, or related engineering field.
• Clear written English and ability to explain technical reasoning concisely.

Responsibilities

• Contribute domain expertise to build high-quality training and evaluation data.
• Review and evaluate AI-generated scientific reasoning for accuracy.
• Design and solve expert-level problems in your area of specialization.
• Rate and rank model outputs against scientific criteria with clear written reasoning.
• Structure knowledge into model-ready data (procedures, results, data).
• Deliver reliable work within defined timelines.

Skills

Inorganic synthesis

Materials characterization

Device fabrication

Advanced packaging

English communication

Education

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

Tools

XRD

SEM

TEM

Spectroscopy

Job description

Zekai seeks experimental scientists and engineers across inorganic synthesis, characterization, superconductors, and semiconductors to support a frontier AI research lab building models for materials science and the physical sciences. This is hands-on, expert-level work requiring deep, specialized knowledge to generate, structure, and evaluate scientific data for model learning.

Remote, US-based engagement up to 40 hours/week for a long-term contract.