NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It’s a unique legacy of innovation that’s fueled by great technology—and amazing people.
Join 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 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, with 12+ years of experience
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.