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Semiconductors, Artificial Intelligence, Computer Hardware, Software Development

Senior Software Engineer, AI Networking

California, United StatesRemoteFull TimeSenior$184,000–$356,500 /yrPosted 2 months agoVisa sponsorship available

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Role summary

NVIDIA is seeking a Senior Software Engineer to join its US-based AI Networking team. This technical leadership role involves transforming AI networking systems, managing complex customer engagements, and influencing product and architecture direction. The engineer will establish expertise in BlueField DPU and ConnectX products, architecting and developing hardware-accelerated software solutions. Key responsibilities include leading technical engagements with hyperscalers, driving performance and reliability improvements, and translating customer needs into product roadmaps. The role requires deep knowledge of networking protocols, distributed systems, low-level software development in C/C++, and system-level debugging.

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. As an NVIDIAN, you’ll be immersed in a diverse, supportive environment where everyone is inspired to do their best work. Come join the team and see how you can make a lasting impact on the world.
We are seeking an outstanding Software Engineer to join our US-based networking software team. As a technical leader, you will lead the transformation of AI networking systems. You will apply your deep expertise to manage complex customer engagements and help develop our product and architecture direction. This role offers an outstanding opportunity to influence NVIDIA's networking technologies and make a significant impact on the industry.
What You’ll Be Doing

  • Establish yourself as a technical specialist in AI networking products, specifically the BlueField DPU and ConnectX product lines. Architect, design, and develop innovative, scalable, and high-performance hardware-accelerated software solutions.
  • Lead deep technical engagements with hyperscalers, involving design-in, coding, bring-up, performance tuning, failure analysis, and production hardening.
  • Partner with internal engineering, product, and architecture teams to transform customer needs into product features, reference architectures, tooling, and guidelines.
  • Drive performance, reliability, and debuggability improvements across customer stacks and translate findings into actionable product, firmware, and software roadmap items.

What We Need To See

  • A Bachelor’s, Master’s or PhD in Software Engineering, Computer Science, Computer Engineering, Electrical Engineering or a related science degree (or equivalent experience)
  • 8+ years of relevant industry experience, including technical leadership across complex systems.
  • Deep knowledge of networking protocols and distributed systems, with a strong understanding of RoCE/InfiniBand, L1–L4 fundamentals, and performance/latency tradeoffs.
  • Proven low-level software expertise with proficiency in C/C++ and comfort debugging across firmware, driver, OS, and application.
  • Demonstrated experience in high-performance networking and system-level debugging, including packet drops, retransmissions, congestion, QoS, ordering, and buffer management.
  • Excellent interpersonal skills, with the ability to clearly explain complex topics to engineers, PMs, and customer collaborators, and align cross-organizational teams toward a decision.
  • Result driven and comfortable multitasking in a dynamic environment with shifting priorities and changing requirements

Ways To Stand Out From The Crowd

  • Prior experience in customer-facing technical leadership at hyperscalers/CSPs.
  • Hands-on expertise with RDMA verbs, DPDK, DOCA, NCCL, CUDA-aware networking, congestion control, and performance tuning at scale.
  • Experience building internal tools, telemetry, and automation that improve triage speed and operational excellence.
  • Experience leading multi-team initiatives across geo/time zones, with clear examples of influence without authority as well as eager and proactive in bringing to bear AI-powered tools to accelerate debugging, documentation, and day-to-day engineering efficiency while maintaining strong engineering judgment.

With competitive salaries and a generous benefits package, 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 and, due to unprecedented growth, our exclusive engineering teams are rapidly growing. If you're a creative and autonomous engineer with a real passion for technology, we want 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 184,000 USD - 287,500 USD for Level 4, and 224,000 USD - 356,500 USD for Level 5.
You will also be eligible for equity and benefits.
Applications for this job will be accepted at least until March 26, 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.
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Sample NVIDIA interview questions

  • 1

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  • 2

    Implement a distributed data migration management platform.

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  • 3

    Develop a distributed tracing system for tracking and debugging.

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  • 4

    Design a distributed training system for a trillion-parameter language model

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  • 5

    Design a system for an automation framework to generate a consent form using multiple agents

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