Materials Scientist for AI Model Training [Remote]

Apply your materials science expertise to inform and train next-generation AI systems by analyzing experimental data, annotating technical datasets, and developing realistic case studies that reflect practical challenges in materials engineering. This remote contractor role focuses on converting real-world scientific knowledge into high-quality inputs that improve how models learn and reason. No prior AI experience is required.

• Analyze and interpret scientific data from experiments, technical datasets, and research publications in materials science and engineering.
• Conduct comprehensive technical literature reviews to identify advances, methodologies, and challenges in materials characterization and related areas.
• Annotate and structure technical datasets with precise, detailed commentary and context to support model training.
• Develop realistic scenarios and case studies that represent practical applications and challenges within materials engineering, metallurgy, or related sectors.
• Provide clear, well organized written and verbal explanations of materials phenomena, properties, and scientific reasoning.
• Perform quality assurance checks on scientific deliverables to ensure consistency, accuracy, and adherence to project specifications.
• Collaborate remotely with other scientific contributors using standard digital documentation and communication tools.

• MS or PhD in Materials Science and Engineering, Metallurgy, Mechanical Engineering, Chemical Engineering, or a related discipline with materials specialization preferred.
• Demonstrated expertise in materials characterization techniques, for example microscopy, spectroscopy, and mechanical testing.
• Strong analytical skills and experience interpreting complex scientific data.
• Substantial experience conducting technical literature reviews and summarizing key findings.
• Proven ability to communicate complex technical concepts clearly, both in writing and verbally, to diverse audiences.
• Experience with quality assurance and review of scientific documents or datasets.
• Familiarity with remote collaboration tools and digital knowledge sharing environments.

• Role type: Contractor, fully remote.
• Work involves preparing and submitting task-based deliverables according to project specifications.
• Minimum submission requirements apply. Experts must submit a minimum of tasks per week.
• Start availability: candidates should be ready to begin quickly; roles are typically filled within 48 hours.

• Pay rate: $80.00 to $130.00 per hour.
• Payment model: output-based, experts are paid per task that meets project specifications. The time required to complete work may vary by experience and workflow.

• No prior AI experience required, domain expertise is the priority.
• If selected, you will complete onboarding, and you should be prepared to start your first tasks within 24 to 48 hours after onboarding is finished.