Senior GPU Memory Architect — Power-Efficient HPC Innovator

NVIDIA Corporation; Santa Clara (CA); On-site; USD 214,000 - 357,000; Full time

Benefits offered by this job

Equity

Benefits

Job summary

NVIDIA Corporation is seeking a world-class computer architect to advance high-performance computing systems with a focus on power-constrained performance. The role emphasizes memory systems, perf/W, and perf/mm, and requires deep expertise in energy efficiency and PPA analysis.

You will model, simulate, and prototype architectures, collaborate with partners, and contribute to cutting-edge GPU memory architectures.

Qualifications

• 10+ years of experience in CPU/GPU architecture with focus on energy efficiency
• Bachelor's degree in Electrical Engineering, Computer Science, or related field
• Expertise in power analysis and modeling in pipeline-based architectures
• Experience with power analysis tools like Ansys PowerArtist, Synopsys PTPX
• Proficiency in C, C++ and scripting languages

Responsibilities

• Develop high-performance processor and system architectures with emphasis on memory systems and energy efficiency
• Improve GPU memory systems to optimize perf/W and perf/mm
• Create architecture prototype models for power and noise analysis
• Conduct performance and power simulations to guide optimizations
• Analyze benchmarks and workloads to identify energy/performance improvements
• Debug power and performance issues across models, RTL, silicon, and systems
• Collaborate with external partners on system infrastructure

Skills

CPU/GPU architecture

Memory systems design

Energy efficiency

Power analysis

C/C++ and scripting

Education

Bachelor's degree in EE/CS or related field

Tools

Ansys PowerArtist

Synopsys PTPX

Job description

NVIDIA Corporation is seeking a world-class computer architect to advance high-performance computing systems with a focus on power-constrained performance. The role emphasizes memory systems, perf/W, and perf/mm, and requires deep expertise in energy efficiency and PPA analysis.

You will model, simulate, and prototype architectures, collaborate with partners, and contribute to cutting-edge GPU memory architectures.