Principal Architect, AI Networking at NVIDIA

Santa Clara, California, United States

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Not SpecifiedCompensation

Expert & Leadership (9+ years)Experience Level

Full TimeJob Type

UnknownVisa

Artificial Intelligence, Networking, TechnologyIndustries

Requirements

Master's or Ph.D. in Computer Science, Electrical or Computer Engineering from a top-tier university (or related field) (or equivalent experience)
12+ years of relevant academic or proven experience in the field
Comprehensive understanding of AI workloads (primarily inference, but also training) and their impact on network infrastructure
Strong proficiency in Machine Learning/Deep Learning fundamentals, inference runtimes, and Deep Learning frameworks
Skilled in C or C++ for systems software development; familiarity with Rust is helpful
Curiosity for building leading edge technology
Ability to work and communicate effectively across diverse teams with varying expertise and time zones

Responsibilities

Work on accelerating NVIDIA Dynamo - KV cache management and large-scale inference
Developing and researching groundbreaking networking technologies to advance and scale AI networks
Co-designing software and hardware networking solutions across various networking related domains, from network transports to AI frameworks
Working closely with NVIDIA's hardware architecture, software architecture, and research teams to build innovative networking hardware and software solutions
Leading the development of prototypes that optimize AI training and inference infrastructure

Skills

Key technologies and capabilities for this role

AI NetworkingKV Cache ManagementLarge-Scale InferenceNetworking TechnologiesNetwork TransportsAI FrameworksHardware ArchitectureSoftware ArchitectureAI TrainingAI Inference

Questions & Answers

Common questions about this position

What is the salary range for the Principal Architect, AI Networking role?

The base salary range is 272,000 USD - 425,000 USD.

Is this position remote or hybrid?

The position is hybrid.

What are the required qualifications and skills for this role?

A Master's or Ph.D. in Computer Science, Electrical or Computer Engineering (or equivalent), 12+ years of relevant experience, understanding of AI workloads, proficiency in ML/DL fundamentals and frameworks, and skills in C or C++ are required.

What is the company culture like at NVIDIA?

NVIDIA offers a diverse, supportive environment where everyone is inspired to do their best work, with a highly dynamic setting focused on innovation and collaboration across teams.

What makes a candidate stand out for this position?

Candidates with a proven research track record, experience in LLM inference, AI network and storage needs, background in storage optimization, and stellar communication skills will 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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