Deep Learning Performance Architect
Mid-level role focused on optimizing deep learning performance across GPU architectures, identifying bottlenecks, and proposing hardware/software improvements for NVIDIA’s high-performance computing systems in Shanghai.
Skills required
About this role
NVIDIA is developing GPU and system architectures that accelerate deep learning and high-performance computing applications. We are looking for an expert deep learning performance architect to join our deep learning modelling, performance projections, analysis and optimization effort. In this position, you will have the chance to analyze deep learning performance on different hardware and software architecture and make a significant impact in a dynamic technology focused company
What you’ll be doing:
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
What we need to see:
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
