• Conduct research on Network Filesystem (NFS) storage and develop a metadata management service, alongside optimizing algorithms for workload-aware data and metadata access.
• Execute system testing to ensure the high availability and reliability of data storage solutions.
• Create problem determination solutions aimed at identifying root causes and resolving issues within the storage environment.
• Collaborate as part of a small, high-performance team, primarily utilizing Python and C++ for development.

Requirements

What you’ll bring to the team:

• Knowledge and experience in AI/LLM (Large Language Models) and storage systems, including operating system structures.
• Strong understanding of file systems and LLM processing, specifically in areas such as metadata layout and LLM inference flow.
• Proficient in UNIX scripting and programming languages like C++ and Python.
• Demonstrated research capabilities with a quick ability to learn new technologies and products.
• Ability to handle complex tasks by assessing issues and breaking down problems to achieve optimal solutions.
• Currently pursuing a Bachelor's or Master's degree in Computer Science, Software Engineering, Computer Engineering, Machine Learning, or related fields.