Nvidia Senior Software Research Architect AI Networking 

Israel, Tel Aviv District, Tel Aviv-Yafo 

762085904

time type

Full time

posted on

Posted 3 Days Ago

job requisition id

computing for more than 25 years.a unique legacy of innovationfueled by great technology—and amazing people. Today,

You will define how AI models are deployed and scaled in production using the NVIDIA Spectrum-X Networking Platform, influencing decisions from inter-node communication and

Be Doing:

• Lead research and development of end-to-end networking solutions for distributed AI training and inference at scale, with a focus on job completion time, failure resiliency, telemetry, scheduling, andplacement.

• Analyze current deployments, develop prototypes, and recommend architectural improvements.

• Stay abreast of the latest research; become the team’s authority in emerging networking techniques and technologies.

• Design, simulate, and validate new systems using novel, scalable network simulator NSX.

• Develop and test prototypes on large-scale GPU clusters (e.g., Israel-1).

• Collaborate across hardware, firmware, and software teams to translate ideas into real networking product features.

• Publish patents and present research at leading conferences.

What We Need to See:

• M.Sc. or PhD (preferred) in Computer Science, Electrical/Computer Engineering, or related field—or B.Sc. with research experience andpublications.

• 5+ years of relevant experience.

• Deep expertise in networking and communication internals (NCCL, RDMA, congestion control, routing).

• Strong software engineering skills in C++ and/or Python.

• Excellent system-level design and problem-solving abilities.

• Outstanding communication and collaboration skills across technical domains.

Ways to Stand Out from the Crowd:

• Proven passion for solving sophisticated technical problems and delivering impactful solutions.

• Record of publications in top-tier conferences.

• Experience in designing and building large-scale AI training clusters.

• Post-PhD research experience

• Practical understanding of deep learning systems, GPU acceleration, and AI model execution flows.