The job in two lines
This role involves shaping and optimizing GPU architectures to improve product yield and performance, and developing tools and models to capture architectural and performance requirements.
Summary by Rezifi's AI, from NVIDIA’s posting. Years and pay appear only when the posting states them.
What you'd do
- Shape GPU architectures to improve product yield and performance
- Analyze manufacturing defects and develop methods to isolate or disable affected regions
- Build software tools and models for architectural, performance, and product requirements
- Develop optimization techniques for large configuration spaces
- Evaluate yield, performance, area, implementation cost, complexity, and product flexibility
- Work across architecture, performance, design, silicon, Operations, and software teams
Skills it is built around
- GPU Architecture
- C++
- Python
- architecture
- performance
- product yield
Required
- computer engineering
- computer science
- electrical engineering
- area
- cost
- complexity
- Design
- implementation
Nice to have
- gpu
- CPU
- System on Chip (SoC)
- complex processor architecture
- constraint-based reasoning
- Combinatorial Optimization
- mathematical-optimization
- silicon yield
- defect tolerance
- harvesting
- redundancy
- repair
The facts
- Experience
- 10+ years
- From the posting: “10+ years in GPU, CPU, SoC, or complex processor architecture”
- Pay
- $184,000 to $356,500 a year
- NVIDIA’s own figure.
- Level
- Senior
- Field
- GPU architecture
The full posting
From NVIDIA’s careers site
As NVIDIA posted it. See the original
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.
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.More like this
- Senior Mask Design Engineer – HardwareNVIDIA · Santa Clara · Posted 4 weeks ago
- Product Management and Configuration EngineerNVIDIA · Tel Aviv · Posted 4 days ago
- Software Performance EngineerNVIDIA · Yoqneam · Posted 6 days ago
- Infiniband Network Software EngineerNVIDIA · Ra'anana · Posted 10 days ago
- Lead Systems Software Test Engineer – CSP EngagementsNVIDIA · Santa Clara · Posted 12 days ago
- Distinguished Engineer – Data Center System Software ArchitectNVIDIA · Santa Clara · Posted 2 weeks ago