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Senior Performance Engineer - DGX Cloud

NVIDIA Corporation

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Skills named in this posting

  • C++
  • Python
  • CUDA
  • PyTorch / TensorFlow
Joining NVIDIA's DGX Cloud AI Efficiency Team means advancing the performance, efficiency, and resiliency of large-scale AI workloads. We help AI researchers and platform teams understand end-to-end behavior across GPUs, networking, storage, and software stacks. We are seeking a Senior Performance Engineer to characterize workloads, establish performance baselines, diagnose bottlenecks, and drive optimizations from investigation through deployment. Your work will shape scalable DGX Cloud systems, turn complex measurements into prioritized engineering decisions, and continuously raise the performance and reliability of AI workloads. Join our technically diverse team of infrastructure experts to unlock more efficient AI at scale. What you'll be doing: • Analyze end-to-end performance of large-scale AI workloads across compute, network, storage, and software stacks. • Design and execute rigorous performance studies to establish baselines, diagnose regressions, and quantify bottlenecks. • Define performance and efficiency evaluation methodologies, benchmarks, and success metrics for AI workloads. • Use profiling, observability, and data analysis to turn performance measurements into actionable optimization plans. • Partner with deep learning engineers, platform teams, and GPU architects to validate and deliver performance improvements. • Communicate performance findings, tradeoffs, and recommendations clearly to influence system and software design decisions. What we need to see: • BS or higher degree in computer science, computer engineering, or a related field (or equivalent experience). • 12+ years of experience in strong programming skills in C++ and Python, with the ability to build reliable analysis and automation workflows • Solid foundation in operating systems, computer architecture, and distributed systems • Experience with performance engineering, benchmarking, profiling, and optimization of complex software or systems • Ability to communicate technical findings, prioritize high-impact work, and build alignment across teams Ways to stand out from the crowd: • Experience analyzing large-scale AI clusters or distributed training and inference workloads • Experience with CUDA, GPU computing systems, and GPU performance analysis • Hands-on experience with deep learning frameworks such as PyTorch or JAX/XLA • Deep understanding of system-level performance analysis, workload characterization, and optimization NVIDIA leads the way in groundbreaking developments in Artificial Intelligence, High-Performance Computing, and Visualization. The GPU, our invention, serves as the visual cortex of modern computers and is at the heart of our products and services. Our work opens up new universes to explore, enables amazing creativity and discovery, and powers what were once science fiction inventions, from artificial intelligence to autonomous cars. NVIDIA is looking for exceptional people like you to help us accelerate the next wave of artificial intelligence.

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Original posting: jobs.nvidia.com

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RISC-V ecosystem

NVIDIA Corporation in the RISC-V ecosystem

RISC-V International: Premier Board

Founded in 1993, NVIDIA is an AI computing company. The company is headquartered in Santa Clara, California.

  • NVIDIA is bringing CUDA platform support to RISC-V, i.e. allowing a RISC-V CPU to host CUDA GPU applications
  • Publicly credited the RVA23 profile as the enabler: "We wouldn't have considered porting CUDA to RISC-V without it"
  • Active in RISC-V International profile/standards work and a frequent presence in RISC-V ecosystem coverage

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