ByteDance Server platform team is responsible for architecting, designing, and building the best server and storage system to meet the requirements of high-performance, low cost and easy to operate.
Requirements
- 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 a 12-week full-time work period during Fall 2026
- Please state your availability clearly in your resume (Start date, End date).
- Candidates can apply to a maximum of two positions and will be considered for jobs in the order you apply.
- Applications will be reviewed on a rolling basis - we encourage you to apply early.
