Senior Software Engineer, Network System Validation
NVIDIA is hiring a Senior Software Engineer, Network System Validation. Level rates it ; you can apply on NVIDIA.
Level's read on this job
- On Level's scale, this software engineer role is Works on AI ●●●○: the daily work is on AI products, without building the model.
- The posting mentions Python, C and Nccl among its tools and skills.
- Level classes it as a senior role.
- NVIDIA has 2,700+ other open roles on Level.
AI in this role
Lead the validation of advanced high-speed networking solutions and performance analysis across complex large-scale AI cluster environments.
NVIDIA is shaping the next era of computing, where AI, accelerated computing, and high-speed networking come together to power the world’s most advanced AI systems. Within NVIDIA, the Networking Business Unit (NBU) builds the high-speed interconnect technologies — Ethernet, InfiniBand, NVLink, and BlueField DPUs — that connect thousands of GPUs into a single AI supercomputer.
NVIDIA is looking for a Technical Lead to join our Network System Validation group and lead the validation of advanced networking solutions across complex AI cluster environments. This is a deeply hands-on technical leadership role, combining ownership of the validation roadmap with technical mentoring and engineering excellence. You will develop validation methodologies and automation frameworks, while working hands-on on debugging, performance analysis, and cutting-edge AI networking technologies at scale. Join us to help push NVIDIA’s networking technologies to their limits and shape how next-generation AI infrastructure is validated.
What you’ll be doing:
Review system and product requirements, design validation methodologies, develop and implement comprehensive test plans, functional and performance, for networking technologies in large-scale AI cluster solutions
Develop and maintain benchmarks, automation tools and scripts for test execution, environment setup, log collection, and data analysis.
Lead end-to-end investigation of complex issues by reproducing real-world scenarios, analyzing logs, telemetry, packet captures, and system metrics to identify functional issues and performance bottlenecks, triaging problems across the hardware and software stack, and driving them to root cause and resolution
Read and understand source code (C/C++/Python) to investigate defects, validate fixes, and improve logging, instrumentation, and debugging capabilities
Collaborate deeply with software and hardware development teams to debug networking technologies, including NCCL, RoCE, RDMA, and related software components using targeted experiments and code inspection
Profile and research AI training and inference workloads, correlating application behavior with network and system telemetry to identify scalability and performance limitations
Document findings, communicate technical results, and continuously improve validation methodologies, automation environments, and engineering processes
What we need to see:
B.Sc. / B.A. in Computer Science, Electrical Engineering, or equivalent experience
8+ years of experience in networking, system validation, or related domains
Proven experience debugging complex production systems by forming hypotheses, designing experiments, and driving issues to root cause
Ability to read, debug, and reason about C/C++ code (Rust or Go a plus)
Strong scripting and automation experience using Python, Bash, and/or Ansible
Deep understanding of distributed systems: concurrency, consistency models, fault tolerance, and large-scale system performance under stress
Ability to drive technical alignment across teams, communicate tradeoffs clearly, and make high-quality architectural decisions at speed
Advance AI-driven approaches to test automation: intelligent scenario generation, LLM-augmented root-cause analysis, and autonomous validation pipelines
Ways to stand out from the crowd:
Experience with large-scale clusters or distributed systems
Familiarity with NVIDIA networking solutions (ConnectX, SpecX, BlueField)
Background in performance analysis, Kubernetes, or cloud environments
Background in chaos testing, fault injection, or simulation systems
We have some of the most forward-thinking and hardworking people 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, disability status or any other characteristic protected by law.
How we rate this
Senior Software Engineer, Network System Validation at NVIDIA rates 65 out of 100 for how much of the daily work is AI. That makes it Works on AI (AI Level 3 of 4). The level is about AI in the job, not seniority.
Works on AI. The daily work is on AI products, without building the model.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.
Prepare for this job
Built from this posting and from similar jobs on Level.
Skills and AI tools this role asks for
Also common in software engineer jobs at this level
Pay
- Typical software engineer job
- $168k
This posting doesn't list pay. Use the typical software engineer figure when pay comes up. See software engineer jobs
Questions you could be asked
- Tell me about a project where system validation was part of your work. What did you do?
- Tell me about a project where networking was part of your work. What did you do?
- Tell me about a project where distributed systems was part of your work. What did you do?
- Tell me about a project where performance analysis was part of your work. What did you do?
- Tell me about a project where debugging was part of your work. What did you do?
Adapt your resume
- List these exact terms on your resume: System Validation, Networking, Distributed Systems, Performance Analysis, and Debugging. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
- Show where AI is part of your daily process, not a one-off project. This role expects it to be a running habit.
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