Qualcomm
GPU Power Analysis Engineer
$170K–$254K
San Diego, California · On-site · Full-time · Posted Sep 17, 2026
- Experience
- Bachelor's degree: 4+ years; master's degree: 3+ years; PhD: 2+ years of relevant software, hardware, systems engineering, or related work experience. Preferred skills also state 3 to 5 years of relevant experience.
- Education
- Bachelor's, master's, or PhD in Computer Engineering, Computer Science, Electrical Engineering, or a related field.
About the job
Analyzes GPU and system-level performance and power efficiency to guide power projections and improve next-generation GPU and SoC designs.
What you'll do
- Analyze and model performance and power efficiency for graphics and AI workloads, identifying opportunities to improve performance per watt.
- Develop scalable power-projection methodologies and tools for GPU/SoC sizing, debug, and validation.
- Conduct competitive performance/power analysis and contribute post-silicon learning to model and architecture improvements.
What they ask for
- Understanding of GPU and/or SoC architecture, common SoC hardware blocks, and power concepts at microarchitecture and system levels.
- Strong programming knowledge, such as Python.
- Analytical and problem-solving skills.
- Fluency in using AI tools for coding and debugging system-level problems.
Nice to have
- Knowledge of graphics APIs or signal-processing techniques.
- Experience in competitive CPU/GPU performance and power analysis or post-silicon debugging.
Pay
$169,500.00 - $254,300.00 USD base salary
Tools
Python
AI focus
Uses AI tools for coding and debugging system-level problems; analyzes power and performance for graphics/AI workloads.
Model-written summary · the original posting is authoritative