The company is looking to solve the problem of developing high-performance, low-cost, and easy to operate server and storage systems.
Requirements
- Master or Ph.D candidate in Electrical Engineering, Computer Engineering, Computer Science or related majors
- Thesis in GPU/AI platform architecture and/or application performance optimization design or software hardware co-design
- Deep understanding of computer system architecture, especially on GPU/AI SoC or Platform Architecture, Interconnect Fabric, and Memory sub-system
- Experienced in GPU/AI system application performance optimization or software hardware co-design
- Strong knowledge and proficiency in software development in C/C++, scripting languages such as Python
- Understand the implementation of GPU/AI virtualization technology, deep learning architecture, and distributed system
Responsibilities
- Develop application benchmarks, tools and performance optimization method for GPU/AI system
- Identify the system bottleneck/opportunity with deep system-level data-driven study, explore innovative options through SW-HW co-design, and lead them towards implementation
- Develop GPU/AI system TCO model, based on application benchmark and performance optimization
- Work with industry consortiums and open standard committees to investigate the emerging standards or technologies, and contribute our research results to the industry
- Work with our technology partners and suppliers to setup POC or prototypes to evaluate and test the new technologies or architectural designs
Other
- Must be able to commit to one of the following start dates
- State availability clearly in your resume (Start date, End date)
- Apply to a maximum of TWO positions and will be considered for jobs in the order you apply
