Senior GPU Architect - Performance and Yield Optimization

NVIDIA; Santa Clara (CA); On-site; USD 184,000 - 357,000; Full time

Benefits offered by this job

Equity

Benefits

Job summary

NVIDIA in Santa Clara, CA seeks an experienced hardware/software architect to shape GPU architectures and optimize multi-die configurations. You will evaluate yield, area, and performance and translate requirements into executable models.

The role requires 10+ years in GPU/CPU/SoC architecture, deep knowledge of GPU pipelines, and strong C++/Python skills to build simulators and optimization tools. Equity and benefits are offered; applications accepted until 2026-09-19.

Qualifications

• BS, MS, or PhD in Computer Engineering, Computer Science, Electrical Engineering, or related field, or equivalent experience, plus 10+ years in GPU, CPU, SoC, or complex processor architecture.
• Strong understanding of GPU architecture, 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, yield, area, cost, and complexity tradeoffs and influence decisions across teams.

Responsibilities

• Shape GPU architectures that improve product yield while maintaining performance and architectural simplicity.
• Analyze how manufacturing defects affect architectural resources, then develop methods that isolate or disable affected regions while preserving useful functionality.
• Build software tools and models that capture architectural, performance, and product requirements as rules and constraints.
• Develop efficient optimization techniques that explore large configuration spaces and identify viable product configurations.
• Develop approaches for multi-die architectures that improve silicon utilization while meeting product and performance requirements.
• Evaluate yield, performance, area, implementation cost, complexity, and product flexibility, then move proposals into production.

Skills

C++

Python

Architectural models

Simulators

Optimization frameworks

Engineering analysis tools

Education

BS, MS, or PhD in Computer Engineering, Computer Science, Electrical Engineering, or related field

Job description

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It's a unique legacy of innovation that's fueled by great technology-and amazing people. Today, we're tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what's never been done before takes vision, innovation, and the world's best talent. As an NVIDIAN, you'll be immersed in a diverse, supportive environment where everyone is inspired to do their best work. Come join the team and see how you can make a lasting impact on the world.

What You'll Be Doing

• Work with us to shape GPU architectures that improve product yield while maintaining performance and architectural simplicity.
• Analyze how manufacturing defects affect architectural resources, then develop methods that isolate or disable affected regions while preserving useful functionality.
• Build software tools and models that capture architectural, performance, and product requirements as rules and constraints.
• Develop efficient optimization techniques that explore large configuration spaces and identify viable product configurations.
• Develop approaches for multi-die architectures that improve utilization of available silicon while meeting product and performance requirements.
• Evaluate yield, performance, area, implementation cost, complexity, and product flexibility, then work across architecture, performance, design, silicon, Operations, and software to move selected proposals into production.

What We Need To See

• 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.

Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 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 September 19, 2026.

This posting is for an existing vacancy.

NVIDIA uses AI tools in its recruiting processes.

NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

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