Principal SoC Architect – AI-centric Memory Subsystem
| Company | Samsung |
|---|---|
| Location | Austin, TX, USA, San Jose, CA, USA |
| Salary | $216521 – $359527 |
| Type | Full-Time |
| Degrees | Bachelor’s, Master’s, PhD |
| Experience Level | Expert or higher |
Requirements
- 15+ years of experience with a Bachelor’s Degree in Computer Science/Engineering, or 13+ years of experience with a Master’s Degree, or 11+ years of experience with a PhD
- Extensive experience in architecture analysis and performance modeling, ranging from simple analytical models to complex cycle accurate performance model and correlation, especially around CPU – memory subsystems
- High proficiency in leveraging existing simulation capabilities or create new simulation capabilities where necessary
- Detailed knowledge of ODML for LLM as well as traditional CPU/GPU/NPU ML acceleration a big plus
- Detailed knowledge of cache subsystems including caching policies and understanding the tradeoffs of latency, bandwidth and hierarchies
- Detailed knowledge of memory subsystem design to include existing/emerging JEDEC memory standards
- Knowledge of in Interconnect and bus protocols – CHI/ACE interconnect experience preferred
- Strong written and verbal communication skills
- Knowledge of high performance, high efficiency design
Responsibilities
- Drive the definition of SoC memory and cache subsystems for next-generation mobile products with a heavy focus on supporting On-Device ML
- Identify and analyze emerging use cases, as well as proposing new and innovative SoC memory architectures to efficiently support them
- Perform high-level performance modeling and analysis of hardware features, applications, benchmarks, and complex uses cases
- Create necessary simulation/analysis tools to evaluate complex memory subsystem use cases such as gaming and camera use cases
- Deliver architecture proposals and specifications to the design team
- Drive cross-company collaboration by communicating and articulating architecture proposals clearly and effectively, across audiences ranging from hardware software engineers to architecture community peers, and to technology leadership
Preferred Qualifications
- Experience with the Android Ecosystem and analysis tools is a plus
- Experience with Arm Architecture and ecosystem is a plus
- Detailed knowledge of ODML for LLM as well as traditional CPU/GPU/NPU ML acceleration a big plus