Nvidia Principal Architect AI Networking 

United States, Texas 

797644298

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.