GPU/AI Application Platform Engineer Intern – Server Platform – PhD
| Company | ByteDance |
|---|---|
| Location | San Jose, CA, USA |
| Salary | $Not Provided – $Not Provided |
| Type | Internship |
| Degrees | Master’s, PhD |
| Experience Level | Internship |
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.
Preferred Qualifications
-
No preferred qualifications provided.