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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior Performance Engineer - DGX Cloud - **Company:** NVIDIA Ltd. - **Location:** Santa Clara, CA, United States - **Experience:** Expert - **Salary:** $224,000.0 - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Data Analysis, C++ (Programming Language), Cloud Computing, Profiling, Nvidia CUDA, Computer Programming, Computer Engineering, Distributed Computing Environment, Distributed Systems, General-Purpose Computing on Graphics Processing Units, Python (Programming Language), Software Engineering, Graphics Processing Unit (GPU), Cloud Platform System, Pytorch, Deep Learning, Information Technology - **Published:** July 29, 2026 - **Apply:** https://www.disabledperson.com/jobs/73912868-senior-performance-engineer-dgx-cloud ## About the Role * 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 ## Description 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. ## Related Videos - [Coffee with Developers - Stephen Jones - NVIDIA](https://www.wearedevelopers.com/videos/1303-coffee-with-developers-stephen-jones-nvidia) - [Your Next AI Needs 10,000 GPUs. Now What?](https://www.wearedevelopers.com/videos/1590-your-next-ai-needs-10-000-gpus-now-what) - [Profiling Symfony & PHP apps with Blackfire](https://www.wearedevelopers.com/videos/265-profiling-symfony-php-apps-with-blackfire) - [Photonic Computing: Programming a New Class of AI Accelerators (incl. Live Coding)](https://www.wearedevelopers.com/videos/100196-photonic-computing-programming-a-new-class-of-ai-accelerators-incl-live-coding) - [Accelerating Python on GPUs](https://www.wearedevelopers.com/videos/859-accelerating-python-on-gpus) - [A Deep Dive on How To Leverage the NVIDIA GB200 for Ultra-Fast Training and Inference on Kubernetes](https://www.wearedevelopers.com/videos/1625-a-deep-dive-on-how-to-leverage-the-nvidia-gb200-for-ultra-fast-training-and-inference-on-kubernetes) ## Related Articles - [Got AI ideas but no money? Here are 10 free ways to level up your AI skills with Google Cloud](https://www.wearedevelopers.com/magazine/600-got-ai-ideas-but-no-money-here-are-10-free-ways-to-level-up-your-ai-skills-with-google-cloud) - [7 Cloud Computing Trends Coming in 2025 for Developers](https://www.wearedevelopers.com/magazine/412-7-cloud-computing-trends-coming-in-2025-for-developers) - [Best US AI Conferences for CTOs in 2026: Build vs. Buy, Vendor Evaluation, and Peer Intelligence](https://www.wearedevelopers.com/magazine/736-best-us-ai-conferences-for-ctos-in-2026-build-vs-buy-vendor-evaluation-and-peer-intelligence) - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers) - [Stephan Gillich - Bringing AI Everywhere](https://www.wearedevelopers.com/magazine/489-stephan-gillich-bringing-ai-everywhere)