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Networking Solution Test Engineer - AI Cluster Debugging Experience: Not Available to Not Available years Location: Shanghai, China Skills: Linux, Ethernet, NIC, DPU, Switch, NCCL, RoCE, RDMA, C, C++, Python, Bash, Ansible, perf, tcpdump, ethtool, iproute2, AI networking libraries, deep learning, large-scale AI clusters, congestion control, lossless Ethernet, DCQCN, ECN, PFC, BlueField, ConnectX NICs Company Overview We are looking for a networking test engineer with strong systemlevel debugging skills to join our EndtoEnd Verification team. You will work on cuttingedge Ethernetbased AI clusters, owning complex issues across hardware, system software and AI workloads. What youll be doing Design and review test and product requirements across the Ethernet / NIC / DPU / Switch portfolio, focusing on largescale AI cluster behavior. Build and maintain realistic customerlike testbeds, including heterogeneous hardware, OS / driver combinations and complex network fabrics. Own endtoend cluster troubleshooting: reproduce customer scenarios, triage across the stack and drive issues to root cause and fix. Read and understand relevant source code to identify defects, validate fixes and improve logging and instrumentation. Collaborate closely with development teams to debug NCCL, RoCE/RDMA and related networking components using logs, code inspection and targeted experiments. Define tests and guide the automation team to implement robust suites that produce actionable logs, metrics and traces. Run Regression, Performance, Functional and Scale testing, analyze results and provide clear, datadriven reports to stakeholders. Profile and benchmark deep learning training and inference workloads, correlating modellevel metrics with system and network telemetry to uncover bottlenecks. What we need to see B.A./B.Sc. in Computer Science, Electrical Engineering, or equivalent IT/Network/Systems experience. 2 + years of handson networking or systemlevel testing and debugging on Linux. Strong Linux networking and debugging skills (for example perf, tcpdump, ethtool, iproute2). Proven productiongrade debugging experience: forming hypotheses, running experiments, and driving issues to root cause under pressure. Expertise in hostside NIC validation and tuning (offloads, queues, interrupts, firmware/driver interactions). Strong knowledge of AI networking libraries (such as NCCL) and protocols (such as RoCE and RDMA), including performance and correctness debugging. Ability to read and reason about source code (C/C++/Python or similar) and collaborate closely with developers on fixes. Solid scripting and automation skills with Bash / Python / Ansible for setup, log collection, and experiment orchestration. Fast learner, familiar with modern AI tools and workflows, able to adapt quickly. Excellent analytical, problemsolving and communication skills, with strong ownership and a team-oriented mindset. Ways to stand out from the crowd Handson debugging of collective communication libraries (for example NCCL) or largescale LLM training / inference clusters. Experience with large cluster environments (tens to thousands of GPUs or nodes), including incident response and postmortem analysis. Deep expertise in tuning and debugging congestion control and lossless Ethernet for AI workloads (for example DCQCN, ECN, PFC). Familiarity with NVIDIA networking technologies (for example BlueField / BF3, ConnectX NICs) and their software stack and diagnostics. Experience debugging issues that span multiple layers (L2/L3, transport, AI frameworks) or contributing to opensource networking / AI systems. NVIDIA is widely considered to be one of the technology worlds 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. .
Here's how to pick the right one and stand out in your application.
144.883Jobs
31.687IN
81%EN
That number is real. WorkMundi's database shows 144,883 open engineer roles across the world. India has the most with 31,687 jobs, followed by the United States with 30,084. If you just finished reading one job ad and felt paralyzed by choice, you're not alone—but this scale is actually an advantage. It means you can afford to be selective.
Start by geography and language. The majority of engineer ads—117,837 of them—have the job posting text written in English. Use that as one filter, but remember: the ad text language tells you nothing about whether the role actually requires you to speak English day-to-day. Read the job description carefully. Then check which countries have the volume you're targeting. Singapore, Poland, and Australia round out the top five after India and the US.
Next, learn who's hiring. Accenture has posted 2,801 engineer roles. andurilindustries, speechify, and jobgether are also actively recruiting. If you're applying to one of these names, research their hiring patterns and interview style before you apply. That homework pays off.
When you interview, expect the question every engineer hears: 'Tell me about a time you had to debug a problem that wasn't in your job description.' Have a specific story ready—not a general one. Name the tools, the deadline pressure, and what you learned. Hiring managers listen for whether you see problem-solving as part of the role itself, not a favour.