Senior Cloud Performance Architect

4 weeks ago

Santa Clara, California, United States NVIDIA Full time

NVIDIA is seeking a highly skilled Cloud AI Infrastructure Engineer to drive the performance analysis, optimization, and modeling of NVIDIA DGXTM Cloud clusters.

The ideal candidate will have a deep understanding of the methodology to conduct end-to-end performance analysis of critical AI applications running on large-scale parallel and distributed systems.

Candidates will work closely with multi-functional teams to define DGX Cloud cluster architecture for different cloud service providers, optimize workloads running on these systems, and develop the methodology that will drive the HW-SW codesign cycle to develop elite AI infrastructure at scale and make it more easily consumable by users.

Key Responsibilities:

  • Develop benchmarks, end-to-end customer applications running at scale, instrumented for performance measurements, tracking, and sampling to measure and optimize performance of meaningful applications and services.
  • Construct carefully designed experiments to analyze, study, and develop critical insights into performance bottlenecks and dependencies from an end-to-end perspective.
  • Develop ideas on how to improve the end-to-end system performance and usability by leading changes in the HW or SW (or both).
  • Collaborate with external cloud service providers during the full life cycle of cluster deployment and workload optimization to understand and drive standard methodologies.
  • Collaborate with AI researchers, developers, and application service providers to understand difficulties, requirements, project future needs, and share best practices.
  • Work with a diverse set of large language model workloads and their application areas, such as healthcare, climate modeling, pharmaceuticals, financial futures, genomics, and drug discovery.
  • Develop the vital modeling framework and the total cost of ownership analysis to enable efficient exploration and sweep of the architecture and design space.
  • Develop the methodology needed to drive the engineering analysis to advise the architecture, design, and roadmap of DGX Cloud.

Requirements:

  • 7+ years of proven experience.
  • Ability to work with large-scale parallel and distributed accelerator-based systems.
  • Expertise in optimizing performance and AI workloads on large-scale systems.
  • Experience with performance modeling and benchmarking at scale.
  • Strong background in computer architecture, networking, storage systems, and accelerators.
  • Familiarity with popular AI frameworks, such as PyTorch, TensorFlow, JAX, Megatron-LM, and Tensort-LLM.
  • Experience with AI/ML models and workloads, particularly large language models.
  • Understanding of deep neural networks and their use in emerging AI/ML applications and services.
  • Bachelor's or Master's in Engineering (preferably Electrical Engineering, Computer Engineering, or Computer Science) or equivalent experience.
  • Proficiency in Python, C/C++.
  • Expertise with at least one public cloud infrastructure (GCP, AWS, Azure, OCI, etc.).

Preferred Qualifications:

  • Very high intellectual curiosity.
  • Confidence to dig in as needed.
  • Not afraid of confronting complexity.
  • Able to pick up new areas quickly.
  • Proficiency in CUDA and XLA.
  • Excellent interpersonal skills.
  • PhD (nice to have).

NVIDIA offers competitive salaries and a generous benefits package. We are widely considered to be one of the technology world's most desirable employers. If you're a creative and autonomous engineer with a real passion for technology, we want to hear from you.

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