Materials Scientist: AI Evaluation & Problem-Setting (Remote)

SaidGig; New York (NY); Remote; USD 83,000 - 165,000; Full time

Job summary

SaidGig is seeking a remote materials science specialist to help evaluate and improve advanced AI systems by applying hands-on judgment to real processing, characterization, and performance constraints.

You will create materials science problems based on your work, assess AI-generated structure-property reasoning, and identify cases where a material meets specs in theory but may fail in service because of fatigue, corrosion, or manufacturing limits.

Qualifications

• Graduate degree in materials science or related field with research or industry experience.
• Recent hands-on experience processing and characterizing materials.
• Strong written communication skills for documenting technical reasoning.
• Ability to work through ambiguous assignments and identify unclear instructions.

Responsibilities

• Create materials science problems based on work you have performed, including the material system, processing history, target property, and a reference answer for evaluating model responses.
• Assess AI-generated structure-property reasoning, including whether microstructure supports the stated property, characterization evidence supports the conclusion, and proposed processing conditions are realistic.
• Identify cases where a proposed material may satisfy specifications in theory but fail in service because of fatigue, corrosion, thermal cycling, or manufacturing limitations.

Skills

Hands-on processing experience

Materials characterization

Clear technical communication

Ambiguity tolerance

Education

Graduate degree in materials science or related field

Job description

SaidGig is seeking a remote materials science specialist to help evaluate and improve advanced AI systems by applying hands-on judgment to real processing, characterization, and performance constraints.

You will create materials science problems based on your work, assess AI-generated structure-property reasoning, and identify cases where a material meets specs in theory but may fail in service because of fatigue, corrosion, or manufacturing limits.