AI Insights
NVIDIA

Senior System Software Architect, AI and GPU Networking

NVIDIA · Santa Clara, California, US
full-timestaff (8-20 yrs)Posted 20d ago
Software EngineeringIC4ICOn-siteVisa SponsoredRelocation
StackCC++PythonCUDAGPU programmingNCCLUCXMPINVIDIA DynamoNVIDIA NIXLDeep Learning frameworksPyTorchTensorFlowRDMAInfiniBandSoftware Defined Networking (SDN)HPCvirtualizationdistributed systemsperformance profilingoperating systemscomputer architecturenetworking protocolsstorage systems

Summary

Senior architect role at NVIDIA's AI Networking Research team focused on accelerating AI workloads through GPU networking, transport protocols, and co-designing hardware/software systems for modern AI data centers.

About the role

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 senior architect to join us in shaping the future. Senior 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 Senior architect in the AI Networking Research team, you will explore technological challenges on accelerate networking and building AI data centers. Research new transport functions and semantics for optimizing AI workloads, AI systems communication and accelerations and much more. You will also be leading architectural and development efforts across numerous technological fields, related to the modern AI 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 GPU Networking offerings for accelerating AI workloads, such as NVIDIA Dynamo, NVIDIA NIXL and NVIDIA UCX, tailored to the unique requirements of AI workloads.

  • Co-design hardware features (e.g., in GPUs, DPUs, or interconnects) that accelerate data movement and enable new capabilities for inference and model serving. 

  • Identify and evaluate new technologies, innovations and partner relationships for alignment with our technology roadmap and business value.

  • Lead architecture and design of new technologies and innovations such as runtime systems, communication libraries, AI-specific technologies.

  • Lead proof-of-concept development to evaluate and drive such technologies.

What we need to see:

  • Hold a M.Sc. or Ph.D. in Computer Science, Electrical or Computer Engineering from a leading university (or equivalent experience).

  • 8+ years of industry experience (or equivalent) in system architecture, AI systems architecture, scaling of AI, Parallelism of AI frameworks, or deep learning training workloads.

  • Experienced in algorithm design, system programming, computer architecture and operating systems.

  • Experienced in virtualization, networking and storage.

  • Deep understanding of performance profiling and optimization techniques, together with defining and using hardware features.

  • Strong programming and software development skills.

  • Ability and flexibility to work and communicate effectively in a multi-national, multi-time-zone corporate environment.

Ways to stand out from the crowd:

  • Shown research track record.

  • Have experience and passion for system architecture, CPU/GPU/memory/storage/networking.

  • Stellar communication skills.

  • Knowledge in Deep Learning frameworks and AI communication libraries (NCCL, UCX, MPI and equivalents).

  • Deep understanding of Inference and Training workloads and optimizations, like Prefill/Decode, data parallelism, Tensor parallelism, FDSP and others.

NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most forward-thinking and hardworking people in the world working for us. If you're creative and autonomous, we want to hear from you! 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.

What you'll do

1Enhance NVIDIA GPU Networking offerings (Dynamo, NIXL, UCX) for AI workload acceleration
2Co-design hardware features in GPUs, DPUs, and interconnects to accelerate data movement for inference and model serving
3Identify and evaluate new technologies, innovations, and partner relationships aligned with the technology roadmap
4Lead architecture and design of runtime systems, communication libraries, and AI-specific technologies
5Lead proof-of-concept development to evaluate and validate new technologies
6Research new transport functions and semantics for optimizing AI workloads and system communication
7Contribute to distributed AI, deep learning, HPC, SDN, virtualization, and storage solutions for modern AI data centers

Requirements

8+ years of industry experience in system architecture, AI systems architecture, scaling/parallelism of AI frameworks, or deep learning training workloads
Strong background in algorithm design, system programming, computer architecture, and operating systems
Hands-on experience with virtualization, networking, and storage technologies
Deep expertise in performance profiling, optimization techniques, and hardware feature design
M.Sc. or Ph.D. in Computer Science, Electrical Engineering, or Computer Engineering from a leading university (or equivalent experience)

Nice to have

NCCL
UCX
MPI
Deep Learning frameworks
Inference optimization
Tensor parallelism
FSDP
Prefill/Decode optimization
Data parallelism
Research publication track record

Role overview

Role family
Software Engineering
Level
IC4 — ml_ai
Experience
8–20 years
Type
Individual Contributor
Remote policy
On-site
Visa sponsorship
Available

Tech stack analysis

LANGUAGES
CC++PythonCUDA
FRAMEWORKS
NCCLUCXMPINVIDIA DynamoNVIDIA NIXLPyTorchTensorFlowOpenMPI
INFRASTRUCTURE
InfiniBandRDMADPU (Data Processing Unit)GPU interconnectsSoftware Defined Networking (SDN)NVLinkNVSwitch
TOOLS
performance profiling toolsHPC job schedulersvirtualization platforms

Salary estimate

$220K – $350K
AI-estimated salary range
Confidence78%
Reasoning

Salary not disclosed. Based on NVIDIA's known compensation bands for Staff/Senior Architect-level roles in Santa Clara, CA, total compensation (base + RSU) typically ranges from $220K–$350K+ annually. NVIDIA is known for very competitive RSU grants that can significantly elevate total comp. Base salary alone likely $180K–$240K with RSUs making up a large portion.

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Green flags

5 items
Role is at the frontier of AI infrastructure — GPU networking, inference optimization, and AI data center design — offering exceptional career growth and research impact.growth

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Benefits breakdown

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Hiring insights

JD quality
8/10
Urgency
medium
Autonomy
high
Team size
medium (5-15)

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Red flags

PRO3 items
Multi-national, multi-time-zone environment implies potential for irregular hours to coordinate across global teams.work life balance

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Interview insights

PRO
Rounds
6
Duration
4 wks
Difficulty
very hard
Take-home
No

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Career path

PRO
Next roles
Principal Architect, AI SystemsDistinguished Engineer, GPU NetworkingDirector of AI Infrastructure Engineering

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About the company

NVIDIA is the world's leading designer of GPUs and AI computing platforms. Its chips power everything from gaming and data centers to autonomous vehicles and scientific research. With a market cap exceeding $2 trillion, NVIDIA's CUDA platform and AI accelerators have become the backbone of the global AI revolution.

HQSanta Clara, CA, USA
Interview difficultyvery hard
Build vs Maintainbuild
Cross-functionalYes