AI TLM Performance Modeling
About The Position
You will be involved and participate in building performance modeling platforms and tools for Qualcomm’s SoC hardware aiming for AI /cloud data server applications. These platforms are essential to analyze and validate LLMs and AI workloads for cloud data server applications. In this role, you will work in a dynamic research environment, be part of a multi-disciplinary team of hardware, system engineers collaborating with other internal teams. You will work on performance modeling of Qualcomm’s AI hardware platforms finding optimal hardware architecture, tradeoffs, optimizing LLM frameworks and AI workloads. You will design, develop & test performance modeling platforms and tools for analyzing and optimizing AI workloads to improve the performance and power efficiently on all devices.
Requirements
- Programing in Python, C/C++, SystemC, TLM2.0
- Experience in SoC architecture, DDR memory controller, NOC design/modeling
- Experience in AI workloads and architectures including LLMs and ML networks
- Experience in architecture for machine learning hardware accelerators
- Experience with TensorFlow, Pytorch
- Hands-on experience with performance measuring, analysis of ML networks
- Familiarity of Computer architecture, DSP architecture and hardware(RTL) design/modeling/verification
- Experience with compiler frameworks such as LLVM or GCC
- Bachelor's degree in Computer Science, Engineering, Information Systems, or related field and 4+ years of Hardware Engineering, Software Engineering, Systems Engineering, or related work experience.
- Master's degree in Computer Science, Engineering, Information Systems, or related field and 3+ years of Hardware Engineering, Software Engineering, Systems Engineering, or related work experience.
- PhD in Computer Science, Engineering, Information Systems, or related field and 2+ years of Hardware Engineering, Software Engineering, Systems Engineering, or related work experience.
Responsibilities
- Building performance modeling platforms and tools for Qualcomm’s SoC hardware for AI/cloud data server applications.
- Analyzing and validating LLMs and AI workloads for cloud data server applications.
- Working on performance modeling of Qualcomm’s AI hardware platforms.
- Finding optimal hardware architecture and tradeoffs.
- Optimizing LLM frameworks and AI workloads.
- Designing, developing & testing performance modeling platforms and tools for analyzing and optimizing AI workloads.
- Improving performance and power efficiency on all devices.
Benefits
- Competitive annual discretionary bonus program
- Opportunity for annual RSU grants
- Highly competitive benefits package
Stand Out From the Crowd
Upload your resume and get instant feedback on how well it matches this job.
What This Job Offers
Job Type
Full-time
Career Level
Entry Level
