NVIDIA
Senior GPU Architect, Deep Learning
$184K–$356K
US, CA, Santa Clara +2 · Senior · Full-time · Posted Jan 9, 2026
- Location
- US, CA, Santa Clara
US, TX, Austin
US, NC, Durham - Experience
- 8+ years of relevant industry experience in GPU or other parallel programming architectures, or other equivalent experience.
- Education
- MS in Computer Science, Electrical Engineering, or Computer Engineering, or equivalent experience.
About the job
Design and validate GPU architecture features, tools, and models for deep learning training and inference and other parallel computing workloads.
What you'll do
- Design hardware features for future processing architectures targeting deep learning training and inference.
- Develop and use simulators, analysis tools, tests, and infrastructure to design, validate, and verify architectural features and performance models.
- Advance parallel computation and assess how future parallel programming models affect hardware.
What they ask for
- Experience working with hardware targeted at deep learning or mapping deep learning algorithms to hardware.
- Strong programming ability in C, C++, Perl, and Python.
- Background in computer architecture, parallel processing, signal processing, and/or high performance computing.
Nice to have
- Knowledge of state-of-the-art DL algorithms and attention mechanisms.
Pay
184,000 USD - 287,500 USD base salary (Level 4); 224,000 USD - 356,500 USD base salary (Level 5)
Tools
C, C++, Perl, Python, RTL
AI focus
Develop GPU architecture features for deep learning training and inference, including mapping workloads to current and future hardware.
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