Principal Architect, AI Networking

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5 Locations
In-Office or Remote
Artificial Intelligence • Computer Vision • Hardware • Robotics • Metaverse
The Role

NVIDIA has been redefining computer graphics, PC gaming, and accelerated computing for more than 25 years. It’s a unique legacy of innovation that’s fueled by great technology—and amazing people. We're tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what’s never been done before takes vision, innovation, and the world’s best talent. As an NVIDIAN, you’ll be immersed in a diverse, supportive environment where everyone is inspired to do their best work. Come join the team and see how you can make a lasting impact on the world!

As a Software Architect for AI Networking you will part of a groundbreaking team driving technological innovation! This is an outstanding opportunity to craft the future of AI networking by using cutting-edge technologies to address sophisticated challenges. We work in a highly dynamic environment where your contributions will significantly influence AI infrastructure.

What you'll be doing:

  • 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.

What we need to see:

  • 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.

Ways to stand out from the crowd:

  • Proven research track record

  • Experience in LLM inference, AI network and storage needs.

  • Background in storage and storage optimization: file systems, object store, caches, coherency.⁠

  • ⁠Stellar communication skills.

Widely considered to be one of the technology world’s most desirable employers, NVIDIA offers highly competitive salaries and a comprehensive benefits package. As you plan your future, see what we can offer to you and your family at www.nvidiabenefits.com/

#LI-Hybrid

Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 272,000 USD - 425,500 USD.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until August 22, 2025.NVIDIA is committed to fostering a diverse 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.

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The Company
HQ: Santa Clara, CA
21,960 Employees
Year Founded: 1993

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.”

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