This role is to design, develop and optimize AI platform for enterprises applications. It focuses more on the system-level techniques, such as efficiency, scalability and cost. The responsibilities may include but are not limited to:
- Employing software and hardware co-optimization to improve efficiency and reduce costs of AI applications, such as heterogeneous computing (GPU), memory and storage systems, RMDA, operating system and database kernel optimization
- R&D on system-level frameworks and techniques for machine learning applications, such as our open-source project OpenMLDB, GPU virtualization, computing frameworks employing AI chips, and so on
- Exploring and engaging in innovative work, utilizing cutting-edge technologies to enhance product performance and efficiency.
Requirements:
- Proficiency in at least one object-oriented programming language (such as C++/Java/Python) and experience participating in large-scale projects.
- Solid understanding of computing fundamentals, including data structures, algorithms, operating systems, databases and so on. Familiarity with parallel computing and distributed computing concepts.
- Interest in low-level system technologies and building large-scale products, with a focus on solving system-level technical challenges (such as improving performance and scalability, heterogeneous computing, OS kernel development, etc.)
Preferred skills/experience:
- Any relevant development experience in areas such as heterogeneous computing (GPU), database, OS kernel development, storage systems, distributed computing, Spark, or other big data computing frameworks.
- Achievements in internationally renowned computing competitions, such as ICPC.
- Publication at top-tier conferences in the systems field, such as OSDI, SOSP, HPCA, EuroSys, SC, SIGMOD, VLDB, etc.
- Significant contributions to influential open-source projects (please provide portfolio of relevant contributions).
