Senior GPU Architect, Deep Learning
NVIDIA· Architect
Tel Aviv, Raanana, Yokneamfull-timePosted 3mo ago
About the role
Senior hardware architect to define and drive future GPU architectures for deep learning and accelerated computing, from concept through silicon readiness, with a focus on architectural features, microarchitectural direction, and cross-team collaboration.
Responsibilities
- Define and architect new GPU hardware features for future deep learning and parallel processing workloads.
- Drive microarchitectural exploration across compute pipelines, memory hierarchy, data movement, synchronization, and performance efficiency.
- Analyze workload behavior and translate bottlenecks into architectural requirements and hardware feature proposals.
- Evaluate performance, power, area, complexity, and programmability tradeoffs for new architectural directions.
- Develop and use functional and performance models to study new features and refine the architecture before implementation.
- Work closely with RTL, design, verification, compiler, and software teams to ensure successful execution from architecture definition to productization.
- Create clear architecture specifications, validation plans, and success criteria for the features you define.
- Be ready to learn, dig deep, and work across the full stack when required - from workloads and models to RTL and silicon.
Qualifications
- BS, MS, or PhD in Computer Science, Electrical Engineering, Computer Engineering, or equivalent experience.
- 12+ years of relevant industry experience in GPU architecture, computer architecture, or other parallel processing architectures.
- Strong background in hardware architecture and microarchitecture.
- Experience defining and evaluating architectural features with solid understanding of performance, power, and area tradeoffs.
- Strong programming and scripting skills in C, C++, and Python.
- Experience with architectural modeling, simulation, or performance analysis.
- Background in parallel computing, memory systems, high performance computing, or deep learning acceleration.
- Strong communication skills and the ability to drive technical work across distributed, interdisciplinary teams.
Skills
Required:GPU architecturehardware architectureperformance modelingC/C++/Python
Benefits
- NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most forward-thinking and hardworking people in the world working for us. If you're creative, autonomous, and love a challenge, consider joining our GPU Architecture team and help us build the next generation of AI computing platforms.
Last updated Jul 10, 2026. Interested? Apply on the company site.
About NVIDIA
World Leader in AI Computing
NVIDIA invents the GPU and drives advances in AI, HPC, gaming, creative design, autonomous vehicles, and robotics.
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