{"id":2791221,"url":"https://alion.io/job/nvidia-networking-solution-test-engineer-ai-ib-and-ethernet-cluster-debugging","title":"Networking Solution Test Engineer - AI IB and Ethernet Cluster Debugging","company":{"id":6,"name":"NVIDIA","domain":"nvidia.com","url":"https://alion.io/company/nvidia","size_band":"5000+","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Workday","truth_index":{"grade":"B","score":80,"open_postings":763,"ghost_share":0.026,"stale_share":0.718,"repost_share":0.042,"time_to_fill_p50_days":33,"computed_at":"2026-10-19T05:45:15Z"}},"role":"QA","role_family":"QA","seniority":"junior","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Shanghai, China","Beijing, China"],"countries":["CN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":null,"experience_years_min":2,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Ansible","optional":false},{"name":"Bash","optional":false},{"name":"C++","optional":false},{"name":"InfiniBand","optional":false},{"name":"Linux","optional":false},{"name":"LLM","optional":false},{"name":"NCCL","optional":false},{"name":"Python","optional":false},{"name":"Tcpdump","optional":false}],"status":"live","first_seen_at":"2026-04-07T00:00:00Z","employer_posted_date":"2026-04-07","last_verified_at":"2026-10-18T21:10:26Z","board_verified":true,"closed_at":null,"days_open":196,"trust":{"level":"stale","repost_count":0,"flags":["stale"],"days_open":195},"description":"We are looking for a networking test engineer with strong system-level debugging skills to join our End-to-End Verification team. You will work on cutting-edge Ethernet-based AI clusters, owning complex issues across hardware, system software and AI workloads.\nWhat you’ll be doing:\nDesign and review test and product requirements across the InfiniBand / Ethernet / NIC / DPU / Switch portfolio, focusing on large-scale AI cluster behavior.\n\nBuild and maintain realistic customer-like testbeds, including heterogeneous hardware, OS / driver combinations and complex network fabrics.\n\nOwn end-to-end cluster troubleshooting: reproduce customer scenarios, triage across the stack and drive issues to root cause and fix.\n\nRead and understand relevant source code to identify defects, validate fixes and improve logging and instrumentation.\n\nCollaborate closely with development teams to debug NCCL, RoCE/RDMA and related networking components using logs, code inspection and targeted experiments.\n\nDefine tests and guide the automation team to implement robust suites that produce actionable logs, metrics and traces.\n\nRun Regression, Performance, Functional and Scale testing, analyze results and provide clear, data-driven reports to stakeholders.\n\nProfile and benchmark deep learning training and inference workloads, correlating model-level metrics with system and network telemetry to uncover bottlenecks.\n\nWhat we need to see:\nB.A./B.Sc. in Computer Science, Electrical Engineering, or equivalent IT/Network/Systems experience.\n\n2+ years of hands-on networking or system-level testing and debugging on Linux.\n\nStrong Linux networking and debugging skills (for example perf, tcpdump, ethtool, iproute2).\n\nProven production-grade debugging experience: forming hypotheses, running experiments, and driving issues to root cause under pressure.\n\nExpertise in host-side NIC validation and tuning (offloads, queues, interrupts, firmware/driver interactions).\n\nStrong knowledge of AI networking libraries (such as NCCL) and protocols (such as RoCE and RDMA), including performance and correctness debugging.\n\nAbility to read and reason about source code (C/C++/Python or similar) and collaborate closely with developers on fixes.\n\nSolid scripting and automation skills with Bash / Python / Ansible for setup, log collection, and experiment orchestration.\n\nFast learner, familiar with modern AI tools and workflows, able to adapt quickly.\n\nExcellent analytical, problem-solving and communication skills, with strong ownership and a collaborative mindset.\n\nWays to stand out from the crowd\nHands-on debugging of collective communication libraries (for example NCCL) or large-scale LLM training / inference clusters.\n\nExperience with large cluster environments (tens to thousands of GPUs or nodes), including incident response and post-mortem analysis.\n\nDeep expertise in tuning and debugging congestion control and lossless Ethernet for AI workloads (for example DCQCN, ECN, PFC).\n\nFamiliarity with NVIDIA networking technologies (for example BlueField / BF3, ConnectX NICs) and their software stack and diagnostics.\n\nExperience debugging issues that span multiple layers (L2/L3, transport, AI frameworks) or contributing to open-source networking / AI systems.\n\nNVIDIA 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. 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