Senior Performance Engineer - DGX Cloud

Joining NVIDIA's DGX Cloud AI Efficiency Team means advancing the performance, efficiency, and resiliency of large-scale AI workloads.

You will analyze end-to-end performance of large-scale AI workloads across compute, network, storage, and software stacks.

Your responsibilities will include:

• Designing and executing rigorous performance studies to establish baselines, diagnose regressions, and quantify bottlenecks.
• Defining performance and efficiency evaluation methodologies, benchmarks, and success metrics for AI workloads.
• Using profiling, observability, and data analysis to turn performance measurements into actionable optimization plans.
• Partnering with deep learning engineers, platform teams, and GPU architects to validate and deliver performance improvements.
• Communicating performance findings, tradeoffs, and recommendations clearly to influence system and software design decisions.

To be considered, you will need:

• A 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.
• A solid foundation in operating systems, computer architecture, and distributed systems.
• Experience with performance engineering, benchmarking, profiling, and optimization of complex software or systems.
• The ability to communicate technical findings, prioritize high-impact work, and build alignment across teams.

Experience analyzing large-scale AI clusters or distributed training and inference workloads, experience with CUDA, GPU computing systems, and GPU performance analysis, and hands-on experience with deep learning frameworks such as PyTorch or JAX/XLA will be advantageous.

You will also be eligible for equity and benefits.