Qualcomm
AI TLM Performance Modeling
$162K–$243K
San Diego, California · On-site · Full-time · Posted Sep 25, 2026
- Experience
- Bachelor's degree: 4+ years of relevant work experience; master's degree: 3+ years; PhD: 2+ years.
- Education
- Bachelor's, master's, or PhD in Computer Science, Engineering, Information Systems, or a related field.
About the job
Build and test performance-modeling platforms for Qualcomm AI hardware, evaluating SoC architectures and optimizing LLM frameworks and AI workloads for performance and power efficiency.
What you'll do
- Design, develop, and test tools to analyze and optimize AI workloads.
- Model AI hardware performance and evaluate hardware architecture tradeoffs.
- Collaborate with hardware and systems engineers to analyze and validate LLMs and other AI workloads.
What they ask for
- Programming experience in Python, C/C++, SystemC, and TLM2.0.
- Experience with SoC architecture, DDR memory controllers, and NOC design/modeling.
- Experience with AI workloads and architectures, machine-learning hardware accelerators, and measuring and analyzing ML network performance.
- Experience with TensorFlow and Pytorch; familiarity with computer and DSP architecture, RTL design/modeling/verification, and LLVM or GCC.
Pay
$162,000.00 - $243,000.00 USD base salary
Tools
Python, C/C++, SystemC, TLM2.0, TensorFlow, Pytorch, LLVM, GCC
AI focus
Performance modeling and optimization for AI hardware, LLMs, machine-learning networks, and cloud data-server workloads.
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