SpaceXAI is seeking a Materials Science Tutor to enhance its AI technologies by providing high-quality inputs and labels using specialized software. The role involves collaborating closely with the technical team to support the training of new AI tasks, refining annotation tools, selecting complex materials science problems, and driving significant improvements in model performance. Candidates should be comfortable working remotely and may work full-time or part-time, with contractor options available. The position offers competitive hourly compensation and benefits for U.S.-based employees.
Materials Science Tutor en SpaceXAI
Remoto - Remote
Más vacantes en SpaceXAISalary
USD 45 - 75/hour
Requirements
Skills
- Master’s or PhD in materials science, physics, chemistry, chemical engineering, or a highly related field
- Expertise and specialization in a materials-related subdomain, including but not limited to 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 combined with the capacity to exercise autonomous judgment even when presented with limited data/material
- Strong passion for and commitment to technological advancements and innovation
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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