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Nvidia Senior Software Engineer - Performance 
China, Shanghai 
263268338

Today
China, Shanghai
time type
Full time
posted on
Posted 11 Days Ago
job requisition id

Intelligent machines powered by Artificial Intelligence computers that can learn, reason and interact with people are no longer science fiction. Today, a self-driving car powered by AI can meander through a country road at night and find its way. An AI-powered robot can learn motor skills through trial and error — this is truly an extraordinary time and the era of AI has begun.

What you’ll be doing:
  • Develop, maintain and optimize performance KPIs necessary to deliver NVIDIA’s L2/L3/L4 autonomous driving solutions

  • Devise acceleration strategies and patterns to improve software architecture and its efficiency on our computers with multiple heterogeneous hardware engines while meeting or exceeding product goals

  • Develop highly efficient product code in C++, making use of algorithmic parallelism offered by GPGPU programming (CUDA)/ARM NEON while following quality and safety standards such as defined by MISRA

  • Diagnose and fix performance issues reported on our target platform including on-road & simulation

What we need to see:
  • BS/MS or higher in computer science or a related engineering discipline

  • Excellent C and C++ programming skills

  • 10+ years of relevant industry experience

  • Strong knowledge of programming and debugging techniques, especially for parallel architectures

  • Good understanding of System SW / Operating Systems and Computer architecture

  • Experience with performance analysis, optimizations and benchmarking

  • You have excellent analytical, written and verbal interpersonal skills

Ways to stand out from the crowd:
  • Understanding of Embedded architectures and Real-time operating systems & scheduling

  • Strong mathematical fundamentals, including linear algebra and numerical methods

  • Experience implementing algorithms in Robotics, Computer Vision and/or Machine Learning

  • Software development experience with CUDA/GPGPU or any data parallel architectures