NVIDIA
Senior GPU Architect - Performance and Yield Optimization
$184K–$356K
US, CA, Santa Clara · Senior · Full-time · Posted Oct 14, 2026
- Experience
- 10+ years in GPU, CPU, SoC, or complex processor architecture.
- Education
- BS, MS, or PhD in Computer Engineering, Computer Science, Electrical Engineering, or a related field, or equivalent experience.
About the job
Design GPU architectures and optimization methods that improve product yield while preserving performance, functionality, and architectural simplicity.
What you'll do
- Analyze manufacturing defects and develop ways to isolate or disable affected resources while preserving useful functionality.
- Build software tools and models to express requirements as rules and constraints, and optimize viable product configurations.
- Evaluate yield, performance, area, cost, complexity, and flexibility; collaborate across teams to move selected proposals into production.
What they ask for
- BS, MS, or PhD in Computer Engineering, Computer Science, Electrical Engineering, or a related field, or equivalent experience.
- 10+ years in GPU, CPU, SoC, or complex processor architecture.
- Strong understanding of GPU architecture, execution pipelines, and major subsystem interactions.
- Strong C++ and/or Python skills, with experience building architectural models, simulators, optimization frameworks, or engineering analysis tools.
Nice to have
- Hands-on GPU or large-scale SoC architecture experience; experience with optimization techniques or silicon yield and defect-tolerance concepts.
- Experience with multi-die or chiplet architectures, silicon or manufacturing data, GPU profiling, or carrying concepts into production silicon.
Pay
184,000 USD - 287,500 USD base salary (Level 4); 224,000 USD - 356,500 USD base salary (Level 5)
Tools
C++, Python
AI focus
The role focuses on GPU architecture and yield optimization, not AI development. NVIDIA states that it uses AI tools in its recruiting processes.
Model-written summary · the original posting is authoritative