Principal Software Architect, GPU Networking Research

NVIDIA has been defining computer graphics, PC gaming, and accelerated computing for more than 25 years. With an outstanding legacy of innovation, driven by phenomenal technology, and extraordinary people, NVIDIA is looking for a strong technical principal architect to join us in shaping the future. Principal Architects are innovators who can translate business needs into workable technology solutions. Their expertise is deep and broad. They are hands on, producing both detailed technical work and high-level architectural designs.

As a principal architect in the Advanced Development team, you will explore technological challenges on accelerate networking and building AI data centers as well as research new transport functions and semantics for optimizing AI workloads. You will also be leading architectural and development efforts across numerous technological fields, related to the modern data center, such as distributed AI and deep learning solutions, data analytics, High Performance Computing (HPC), Software Defined Networking (SDN), virtualization, storage, and more.

What You’ll Be Doing

• Enhance NVIDIA's future GPU Networking offerings for accelerating AI workloads.
• Lead vision, architecture and design of such technologies.
• Lead proof-of-concept development to evaluate and drive such technologies.
• Identify and evaluate new technologies, innovations and partner relationships for alignment with our technology roadmap and business value.
• Work with the community and maintainers to drive strategic technologies
  
  

• M.Sc. or Ph.D. in Computer Science, Electrical or Computer Engineering from a leading university (or equivalent experience).
• 15+ years of industry experience (or equivalent) in systems architecture or related fields.
• Experienced in virtualization, networking and storage.
• Experienced in either Windows or Linux drivers, with a very good background of the other OS.
• Deep understanding of performance profiling and optimization techniques, together with defining and using HW offloads.
• A teammate with a can-do attitude, high energy and excellent interpersonal skills.
• Ability and flexibility to work and communicate effectively in a multi-national, multi-time-zone corporate environment.
  
  

• Shown research track record.
• Have experience and passion for system architecture, CPU/GPU/memory/storage/networking.
• Stellar communication skills.
• Knowledge in Deep Learning frameworks