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.
What we need to see:
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
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.
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.
This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.
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.Skills Required
- BS or higher degree in computer science, computer engineering, or related field (or equivalent experience)
- 12+ years of experience with strong programming skills in C++ and Python, capable of building 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
- 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 Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about NVIDIA and has not been reviewed or approved by NVIDIA.
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Equity Value & Accessibility — Equity awards and a discounted ESPP are highlighted as core parts of total compensation, enabling employees to share in the company’s success. Stock-based compensation and the two-year lookback ESPP are consistently described as especially valuable.
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Healthcare Strength — Health coverage is portrayed as robust, with comprehensive medical, dental, and vision options alongside mental health support and on-site care resources. Employer HSA contributions and wellness perks reinforce the depth of the offering.
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Retirement Support — Retirement programs are depicted as strong, featuring a meaningful 401(k) match with Roth options and support for Mega Backdoor Roth contributions. These elements position long-term savings as a notable advantage of the total rewards package.
NVIDIA Insights
What We Do
NVIDIA’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing — with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. Today, NVIDIA is increasingly known as “the AI computing company.”
