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# Senior GPU Architect - Performance and Yield Optimization

- **Company:** NVIDIA Ltd.
- **Location:** Santa Clara, CA, United States
- **Experience:** Expert
- **Salary:** $184,000.0 - $287,500.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Architectural Patterns, C++ (Programming Language), Computer Engineering, Software Debugging, Python (Programming Language), Performance Tuning, Software Engineering, Technical Data Management Systems, Graphics Processing Unit (GPU), Yield Optimization, Information Technology
- **Published:** October 29, 2026
- **Apply:** https://www.careerbuilder.com/job-details/senior-gpu-architect-performance-and-yield-optimization-santa-clara-ca--eaeab880-e552-400b-8b9c-b308c11c369a

## About the Role

GPU (Graphics Processing Unit), Performance Tuning/Optimization, Autonomous Driving Systems, GPU (Graphics Processing Unit), Artificial Intelligence (AI), Architectural Services, Productivity Management, Manufacturing Analysis, Manufacturing Debugging, Develop Methodologies, * 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.

## Description

* 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.