Deep Learning Performance Architect
NVIDIA· Architect
Shanghaifull-timePosted 2mo ago
About the role
NVIDIA role focusing on deep learning performance modelling, projections, analysis and optimization across hardware/software architectures to improve DL workloads and energy efficiency.
Responsibilities
- Analyze performance of various deep learning workloads on different architectures
- Identify architecture and software performance bottlenecks
- Explore new features and system configurations to achieve better performance and energy efficiency
Qualifications
- BSc. MS or PhD in relevant discipline (CS, EE, Math, etc.)
- 3+ years of working experience in relevant directions (e.g., hardware system, datacenter hardware, LLM workloads on data center) will be a plus
- Be familiar with GPU or accelerator-based deep learning platform and software stack
- A strong background in computer architecture
- Experience on system architecture design and performance optimization
- Familiar with machine learning and deep learning frameworks
Skills
Required:Deep learning performance analysisComputer architectureSystem architecture designGPU/accelerator DL stackML/DL frameworks
Last updated Jul 31, 2026. Interested? Apply on the company site.
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