Senior Performance Engineer - DGX Cloud

About the role

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.

Responsibilities

• 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.

Qualifications

• 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.

Skills

• Strong programming skills in C++ and Python.
• Experience with performance engineering, benchmarking, profiling, and optimization.
• Understanding of operating systems, computer architecture, and distributed systems.
• 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.

Benefits

• 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.
• We enable amazing creativity and discovery, and power what were once science fiction inventions, from artificial intelligence to autonomous cars.

Pay

• Base salary range: $224,000 - $356,500 for Level 5, and $272,000 - $431,250 for Level 6.

Schedule

• You will be eligible for equity and benefits.

Contact Information

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

Equal Opportunity Employer

• NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.