The role of Materials Science Tutor at xAI is a remote position that focuses on providing high‑quality input and labels using proprietary annotation software to support the training of AI models in advanced materials science. The tutor works closely with technical staff, refines annotation tools, selects complex materials problems, and interprets evolving instructions to deliver curated data. Candidates are expected to hold a Master’s or PhD in a relevant scientific field and possess strong communication skills, as well as expertise in a specific materials subdomain.
Materials Science Tutor at xAI
Remote - Remote
More jobs at xAISalary
USD 45 - 75/hour
Requirements
Skills
- Master’s or PhD in materials science, physics, chemistry, chemical engineering, or a highly related field
- Expertise in a materials-related subdomain such as energy materials, semiconductors, nanomaterials, metals, alloys, biomaterials, polymers, elastomers, ceramics, or glasses
- Proficiency in reading and writing both in informal and professional English
- Strong ability to navigate various information resources, databases, and online resources
- Outstanding communication, interpersonal, analytical, and organizational capabilities
- Solid reading comprehension skills and autonomous judgment
- Strong passion for technological advancements and innovation
- Advanced expertise in materials science demonstrated by multiple publications or patents, preferably with first‑author papers
- Previous AI tutoring experience
- Teaching experience (professor, teacher, or tutor)
- Experience in technical writing, journalism, or a professional writing setting
Responsibilities
- Use proprietary software applications to provide input/labels on defined projects.
- Support and ensure the delivery of high-quality curated data.
- Play a pivotal role in supporting and contributing to the training of new tasks, working closely with the technical staff to ensure the successful development and implementation of cutting‑edge initiatives/technologies.
- Interact with the technical staff to help improve the design of efficient annotation tools.
- Solve problems that help drive innovation in materials by guiding AI models to enhance research in specialized areas, improving outcomes in scientific discovery and application.
- Choose problems from various fields across materials science that align with your specialization, where you can confidently provide detailed solutions and evaluate model responses.
- Regularly interpret, analyze, and execute tasks based on given instructions.
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