Lead Software Engineer for System Performance Analysis

6 days ago


Shanghai, Shanghai, China NVIDIA Full time

NVIDIA is renowned for its advanced analytical tools that enable engineers to enhance the performance and power efficiency of our products and applications. We are seeking innovative, diligent, and imaginative individuals to join our dynamic software team, which upholds high standards. This software engineering position focuses on creating analytical tools across various operating systems and hardware configurations, ranging from individual systems to extensive data centers.

As a vital member of our software development team, you will design and refine tools and systems for performance and power verification, analysis, and prototyping tasks conducted internally. Collaboration with users from diverse departments such as Architecture, Software, and Development Technology will be essential. Our mission is to provide users with intuitive, comprehensive, and precise insights into workloads and systems, empowering them to identify opportunities in both software and hardware, or to construct high-level models that propose and deliver optimal hardware and software solutions to our clients.

Key Responsibilities:

  • Develop internal performance and power profiling tools for real-world applications operating on NVIDIA products, including GPUs and systems.
  • Create infrastructure or services for the storage, visualization, and analysis of profiling data.
  • Collaborate with users to build and calibrate performance and power models for next-generation hardware or systems.
  • Work alongside architects to suggest new hardware features or enhance existing ones based on real-world use cases.

Qualifications:

  • Bachelor's degree in Computer Science or a related field (or equivalent experience) with a minimum of 5 years in software development.
  • Strong capabilities in software design and implementation.
  • Proficient programming skills in Python, modern C++, or contemporary web application development.
  • Solid understanding of Deep Learning frameworks (such as PyTorch, TensorFlow, Megatron-LM, etc.).
  • Familiarity with version control systems like GIT and P4.
  • Exceptional problem-solving and project management abilities.
  • Adaptability to work in a dynamic environment with evolving requirements.

Preferred Qualifications:

  • Experience in developing Continuous Profiling systems for GPU data centers is a significant advantage.
  • Expertise in analyzing and optimizing Deep Learning application performance.
  • Knowledgeable about GPU or CPU architecture.
  • Resourceful in conducting performance or power analysis for GPU applications.
  • Demonstrated experience contributing to large open-source projects.


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