Senior DGX AI Cloud Performance Analysis Tools Engineer at NVIDIA

Santa Clara, California, United States

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$184,000 – $356,500Compensation

Senior (5 to 8 years)Experience Level

Full TimeJob Type

UnknownVisa

Artificial Intelligence, Cloud Computing, TechnologyIndustries

Requirements

Minimum of 8+ years of experience in software infrastructure and tools
BS or higher degree in computer science or similar (or equivalent experience)
Proficient in multiple languages, including C++ and Python
Solid foundation in operating systems and computer architecture
A passion for “it just works” automation, eliminating repetitive tasks, and enabling team members

Responsibilities

Develop AI performance tools for large-scale AI systems, providing real-time insight into applications performance and system bottlenecks
Conduct in-depth hardware-software performance studies
Define performance and efficiency evaluation methodologies
Automate performance data analysis and visualization to convert profiling data into actionable optimizations
Support deep learning software engineers and GPU architects in their performance analysis efforts
Work with various teams at NVIDIA to incorporate and influence the latest technologies for GPU performance analysis

Skills

Key technologies and capabilities for this role

C++PythonOperating SystemsComputer ArchitecturePerformance AnalysisProfilingData VisualizationAutomationGPUDeep LearningAI Workloads

Questions & Answers

Common questions about this position

What is the salary range for this position?

The base salary range is $184,000 - $356,500 USD.

Is this role remote or does it require office work?

This information is not specified in the job description.

What skills are required for this Senior DGX AI Cloud Performance Analysis Tools Engineer role?

Candidates need 8+ years of experience in software infrastructure and tools, proficiency in C++ and Python, and a solid foundation in operating systems and computer architecture. A BS or higher in computer science (or equivalent) is required, along with a passion for automation.

What is the company culture like at NVIDIA for this team?

The DGX Cloud AI Efficiency Team focuses on optimizing efficiency and resiliency of AI workloads, developing scalable tools, and providing a stable environment for AI researchers to innovate. They emphasize 'it just works' automation and enabling team members.

What makes a candidate stand out for this role?

Experience with large-scale AI clusters, CUDA and GPU computing systems, deep learning frameworks like TensorFlow, PyTorch, or JAX/XLA, and a deep understanding of software performance analysis and optimization will help candidates stand out.

NVIDIA

Designs GPUs and AI computing solutions

About NVIDIA

NVIDIA designs and manufactures graphics processing units (GPUs) and system on a chip units (SoCs) for various markets, including gaming, professional visualization, data centers, and automotive. Their products include GPUs tailored for gaming and professional use, as well as platforms for artificial intelligence (AI) and high-performance computing (HPC) that cater to developers, data scientists, and IT administrators. NVIDIA generates revenue through the sale of hardware, software solutions, and cloud-based services, such as NVIDIA CloudXR and NGC, which enhance experiences in AI, machine learning, and computer vision. What sets NVIDIA apart from competitors is its strong focus on research and development, allowing it to maintain a leadership position in a competitive market. The company's goal is to drive innovation and provide advanced solutions that meet the needs of a diverse clientele, including gamers, researchers, and enterprises.

Santa Clara, CaliforniaHeadquarters

1993Year Founded

$19.5MTotal Funding

IPOCompany Stage

Automotive & Transportation, Enterprise Software, AI & Machine Learning, GamingIndustries

10,001+Employees

Benefits

Company Equity

401(k) Company Match

Risks

Increased competition from AI startups like xAI could challenge NVIDIA's market position.

Serve Robotics' expansion may divert resources from NVIDIA's core GPU and AI businesses.

Integration of VinBrain may pose challenges and distract from NVIDIA's primary operations.

Differentiation

NVIDIA leads in AI and HPC solutions with cutting-edge GPU technology.

The company excels in diverse markets, including gaming, data centers, and autonomous vehicles.

NVIDIA's cloud services, like CloudXR, offer scalable solutions for AI and machine learning.

Upsides

Acquisition of VinBrain enhances NVIDIA's AI capabilities in the healthcare sector.

Investment in Nebius Group boosts NVIDIA's AI infrastructure and cloud platform offerings.

Serve Robotics' expansion, backed by NVIDIA, highlights growth in autonomous delivery services.

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