Nvidia Deep Learning Performance Architect Intern 

China, Shanghai 

144970287

What you’ll be doing:

• Establish deep learning applications and use-cases for performance analysis, modelling, and projections

• Analyzing and proposing both SW and HW optimizations for deep learning applications

• Specify hardware/software configurations and metrics to analyze performance, power, accuracy and resiliency in existing and future uni-processor and multiprocessor configurations

• Collaborate across the company to guide the direction of next-gen deep learning HW/SW by working with architecture, library, and compiler teams

• Build Performance Analysis Infrastructure

What we need to see:

• MS or PhD in relevant discipline (CS, EE, Math)

• Strong background in computer architecture

• Expert mathematical foundation in machine learning and deep learning

• Strong programming skills in C, C++, Perl, or Python

Ways to stand out from the crowd:

• Prior experience working on assembly level performance optimization

• Experience working with deep learning frameworks like TensorFlow and Torch

• Familiarity with GPU computing CUDA

• Background with systems-level performance modeling, profiling, and analysis

• Experience in characterizing and modeling system-level performance, executing comparison studies, and documenting and publishing results