AI Tutor - Materials Science

In this role, you will help enhance Grok by providing high-quality data annotations, labels, and inputs focused on materials science. You will draw on your expertise in areas such as energy materials, semiconductors, nanomaterials, metals and alloys, biomaterials, polymers, ceramics, and glasses to evaluate model outputs, identify errors in structure-property reasoning or processing assumptions, and produce clear, rigorous analyses and explanations. Your work will help train Grok to distinguish flawed or inadequately justified materials science analyses from those that are scientifically accurate, well-grounded, and practically insightful.

• Use proprietary software applications to annotate and label data for designated projects.
• Support the delivery of high-quality, accurate, and well-curated datasets that meet project standards.
• Collaborate with technical teams to develop and train new tasks, contributing to the successful implementation of innovative technologies and initiatives.
• Work closely with technical staff to improve the design, functionality, and efficiency of annotation tools and workflows.
• Advance materials science research by guiding AI models in solving complex scientific problems and supporting scientific discovery and practical applications.
• Select and solve problems across various subfields of materials science aligned with your expertise, providing detailed solutions and critically evaluating AI-generated responses.
• Interpret, analyze, and execute tasks accurately in accordance with established guidelines and project requirements.

BASIC QUALIFICATIONS:

• Master’s or PhD in materials science, physics, chemistry, chemical engineering, or a highly related field.

PREFERRED SKILLS AND EXPERIENCE:

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