Nvidia
Nvidia

60 Nvidia Networking Jobs Hiring Near You

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Identify and shape new project opportunities for NVIDIA GPUs, networking, and software in AI and data center use cases. Collaborate closely with Systems Engineering, Product Management, and Sales to ...

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$129K - $175K/yr

An applied research team within NVIDIA's Networking Systems & Software Architecture group is solving some of AI's hardest infrastructure problems. The team builds systems-level software that moves ...

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Nvidia Jobs Information

What is it like to work at Nvidia?

Nvidia is known for its collaborative and innovative culture, prioritizing teamwork and creativity to drive technological advancements. The company's structure is organized into various teams, including research and development, engineering, and sales, with a focus on fostering open communication and knowledge sharing across departments. Working at Nvidia may appeal to candidates who are passionate about artificial intelligence, graphics, and high-performance computing, as the company offers opportunities to contribute to cutting-edge projects and collaborate with experts in the field.
What are the most popular job types at Nvidia?
    Infographic showing various Networking job openings at Nvidia in the United States as of May 2026, with employment types broken down into 100% Full Time. Highlights an 84% Physical, 14% Hybrid, and 2% Remote job distribution.
    Principal Architect, AI Networking

    Principal Architect, AI Networking

    Nvidia Corporation

    Santa Clara, CA • On-site

    Full-time

    Posted 13 days ago


    Job description

    An applied research team within NVIDIA's Networking Systems & Software Architecture group is solving some of AI's hardest infrastructure problems. The team builds systems-level software that moves data between GPUs, nodes, and storage at the speed modern AI demands-spanning low-level transport optimization, hardware-software co-design, and communication frameworks that plug directly into production AI stacks. The team's charter expands into emerging domains including quantum computing interconnects.
    This Principal Architect role leads the research agenda and architectural direction for how NVIDIA's AI systems communicate at scale-across GPUs, DPUs, NICs, and heterogeneous storage. It requires someone who defines project scope from scratch, publishes original work, and translates research breakthroughs into production-grade software that ships industry-wide!
    What you will be doing:
    • Setting the long-term technical vision for distributed AI communication systems-GPU-to-GPU, GPU-to-storage, and cross-node data movement.
    • Conducting original research and prototyping next-generation networking solutions over RDMA, NVLink, and GPUDirect.
    • Driving hardware-software co-optimization with GPU, DPU, NIC, and network switch. Investigating fundamental bottlenecks in communication runtimes for large-scale AI workloads (KV cache transfer, disaggregated prefill/decode, model parallelism).
    • Integrating networking capabilities into AI serving stacks such as vLLM, SGLang, and TensorRT-LLM.
    • Publishing findings, representing NVIDIA in industry forums and standards bodies, and mentoring senior engineers across the organization.

    What we need to see:
    • 15+ years in systems software and/or networking with deep expertise in high-performance networking (InfiniBand, RoCE, RDMA, NVLink), communication libraries (e.g. NIXL, NCCL, UCX, MPI, NVSHMEM), and GPU accelerated systems, with track record of defining and delivering complex, cross-team technical initiatives from research concept to production.
    • MS, PhD or equivalent experience in Computer Science, Computer Engineering, Electrical Engineering, or a related field.
    • Deep understanding of computer architecture, memory hierarchies, DMA engines, and OS-level networking.
    • Understanding of ML systems concepts-transformer architectures, KV cache mechanics, model parallelism, or distributed training and inference patterns.
    • Proficiency in programming languages such as C, C++, Rust and Python.

    Ways to stand out from the crowd:
    • Knowledge of ML inference frameworks (vLLM, SGLang, TensorRT-LLM) and their communication requirements.
    • CUDA programming and NVIDIA GPU architecture expertise.
    • Proved experience influencing product strategy and technical roadmap at a senior level.
    • Major open-source contributions.

    With competitive salaries and a comprehensive benefits package, NVIDIA is widely regarded as one of the most desirable technology employers in the world. Our teams are composed of some of the most forward-thinking and driven engineers in the industry, and we continue to grow rapidly. If you are a senior data engineer passionate about building large-scale, high-impact data platforms, we'd love to hear from you.
    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 - 431,250 USD.
    You will also be eligible for equity and benefits.
    Applications for this job will be accepted at least until April 27, 2026.
    This posting is for an existing vacancy.
    NVIDIA uses AI tools in its recruiting processes.
    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.

    Nvidia logo

    About Nvidia

    Sourced by ZipRecruiter

    NVIDIA has been transforming 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. Today, 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.

    Industry

    Computer and electronic product manufacturing

    Company size

    10,000+ Employees

    Headquarters location

    Santa Clara, CA, US

    Year founded

    1993