Senior Performance Engineer - DGX Cloud

at Nvidia

USD 224,000-431,200 per year

SENIOR

✅ On-site

Tech Stack
Tag name is followed by "@" symbol and proficiency level value. About proficiency levels:

1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;

3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;

7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;

10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.

AI @ 4 CUDA @ 4 Data Analysis Deep Learning @ 4 Distributed Systems @ 6 GPU @ 4 JAX @ 4 Networking @ 4 Observability Performance Analysis @ 4 Profiling @ 4 PyTorch @ 4 Python @ 7

Details

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.

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.

Requirements

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.

Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 224,000 USD - 356,500 USD for Level 5, and 272,000 USD - 431,250 USD for Level 6.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until August 1, 2026.