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NVIDIA

Designs the chips and software that power AI

Senior AI Training Performance Architect

Applied Machine LearningConfirmed live in the last 24 hours
Full-timeIn-person

About the Job

Requirements

  • PhD in Computer Science, Electrical Engineering, or Computer Systems Engineering, or equivalent experience, with 5 or more years of relevant experience; alternatively, an MS with 8 or more years of experience.
  • Strong background in deep learning and neural networks, particularly training.
  • Solid understanding of computer architecture and familiarity with GPU architecture fundamentals.
  • Proven background in analyzing and tuning application performance.
  • Proven experience with processor- and system-level performance modeling.
  • Proficiency in C++, Python, and CUDA.

Responsibilities

  • Understand, analyze, profile, and optimize AI training workloads on state-of-the-art hardware and software platforms.
  • Identify performance bottlenecks in AI training on GPUs, prioritize them, and solve problems across key AI training workloads.
  • Implement production-quality software across multiple layers of NVIDIA's deep learning platform stack, from drivers to deep learning frameworks.
  • Build and support NVIDIA submissions for MLPerf Training benchmarks.
  • Implement key deep learning training workloads in NVIDIA's proprietary processor and system simulators to enable future architecture studies.
  • Develop tools to automate workload analysis, optimization, and other critical workflows.

About the Company

NVIDIA

Designs the chips and software that power AI

NVIDIA designs the chips and software that power artificial intelligence and sells complete data center systems to cloud providers, AI labs, and other businesses, along with GeForce graphics cards for gamers. Its GPUs, chips that perform thousands of calculations at once, became the main hardware for AI after researchers used them to train the AlexNet image-recognition model in 2012. NVIDIA connects many GPUs with its own processors and networking gear into servers and rack-sized computers, and developers program them through its CUDA software. These systems bring in most of its sales, and it also makes chips for cars and robots. Jensen Huang co-founded NVIDIA in 1993, and it is based in Santa Clara, California.

Company size
10,001+
Company stage
IPO
Headquarters
Santa Clara, CA
Founded
1993

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