Senior GPU Architect, Deep Learning

Experience: Not Available to Not Available years

Location: Tel Aviv, Israel

Skills: GPU architecture, computer architecture, parallel processing architectures, hardware architecture, microarchitecture, C, C++, Python, architectural modeling, simulation, performance analysis, parallel computing, memory systems, high performance computing, deep learning acceleration

What you'll be doing:
Define and architect new GPU hardware features for future deep learning and parallel processing workloads.
Drive microarchitectural exploration across key areas such as compute pipelines, memory hierarchy, data movement, synchronization, and performance efficiency.
Analyze workload behavior and translate bottlenecks into clear 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.

What we need to see:
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.
Robust communication skills and the ability to drive technical work across distributed, interdisciplinary teams.

Ways to stand out from the crowd:
Deep understanding of modern GPU architecture and the interaction between hardware and AI workloads.
Experience with memory subsystem architecture, interconnects, coherence, scheduling, or execution pipelines.
Experience with pre-silicon performance studies, workload characterization, and architectural correlation.
Familiarity with training and inference behavior for large-scale deep learning models.
Experience with silicon bring-up, debug, or post-silicon analysis.

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.

📌 Senior GPU Architect, Deep Learning (Mumbai)
🏢 NVIDIA
📍 Mumbai