- BS, MS, or PhD in Computer Engineering, Computer Science, Electrical Engineering, or a related field, or equivalent experience, plus 10+ years in GPU, CPU, SoC, or complex processor architecture.
- Strong understanding of GPU architecture, the overall execution pipeline, and interactions across major GPU subsystems.
- Strong computer architecture fundamentals and the ability to reason about disabling, isolating, or reconfiguring resources.
- Strong C++ and/or Python skills with experience building architectural models, simulators, optimization frameworks, or engineering analysis tools.
- Experience translating architecture and product requirements into rules, constraints, algorithms, and executable analysis, including complex optimization or configuration problems.
- Ability to quantify performance, product yield, area, cost, and complexity tradeoffs and influence decisions across architecture, design, implementation, and product teams.
Ways to Stand Out From the Crowd
- Hands-on GPU architecture or large-scale SoC architecture experience.
- Experience with constraint-based reasoning, combinatorial optimization, mathematical optimization, or related techniques.
- Background with silicon yield, defect tolerance, harvesting, redundancy, repair, resource isolation, or configurable processor architectures.
- Experience with multi-die, chiplet, or other modular processor architectures and complex resource-allocation problems.
- Experience using silicon or manufacturing data, developing performance or architecture simulators, profiling GPU workloads, or carrying concepts into production silicon.
#ArchitectYourFuture
Your base salary will be determined based on your location, experience, and other objective job-related factors. The expected base salary ranges for this position are: 184,000 USD – 287,500 USD for Level 4; and 224,000 USD – 356,500 USD for Level 5.
You will also be eligible for equity and benefits.
Applications for this job will be accepted at least until November 3, 2026.
This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.