Inorganic Materials Scientist or Engineer for AI Training

SaidGig; New York (NY); À distance; USD 98 000 - 134 000; Plein temps

Résumé du poste

SaidGig is seeking a highly skilled materials scientist to develop training and evaluation data for AI models focused on inorganic materials, superconductors, semiconductors, and advanced packaging. You will apply hands-on experimental methods and structured data practices to generate high-quality, model-ready datasets.

This is a remote, US-based hourly engagement with 10–40 hours per week, long-term in scope.

Qualifications

• PhD or MS in materials science, chemistry, physics, or related engineering discipline; hands-on experience acceptable.
• Clear written English and ability to explain technical reasoning concisely.
• Experience with thin-film growth or device fabrication (MBE/epitaxy, MOCVD, CVD, sputtering, IBAD, etching, clean-room).

Responsabilités

• 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.

Connaissances

Inorganic synthesis

Superconducting materials

Semiconductors & packaging

Materials characterization

XRD

SEM

TEM

Spectroscopy

Device physics

Written English

Formation

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

Outils

MBE / epitaxy

MOCVD

CVD

Sputtering

Etching

Clean-room microfabrication

Description du poste

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.

Qualifications

• 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.

Work Terms

Remote, US-based hourly engagement.Long-term, ongoing work.Commitment ranges from a minimum of 10 hours to up to 40 hours per week.

Compensation

$84 per hour.