Nvidia Senior Networking Test Engineer 

China, Shanghai 

331947770

You are going to be part of the E2E Verification team with the main goal of testing the most exciting High Performance Ethernet AI network. You will interact with HPC, OS, Switch, HCA, CPU and GPU compute, and systems specialist to architect, develop and bring up large scale performance platforms.

What you'll be doing:

• Contribute to design review and product features requirements under the whole Ethernet/ NIC/DPU/Switch portfolio. Design and build setup topologies with an emphasis on an emulation of customer large scale / complex environments.

• Collaborating closely with multi-functional teams, including hardware engineers, software developers, and domain experts, to deliver optimized solutions that meet the demanding requirements of HPC/AI workloads.

• Design, mentorship for testing automation team to implement tests. Generate comprehensive test reports during release execution procedure, assist with reproduction and debugs complex customer use cases, with determination of the issue root cause, be an engineering PIC for the full verification cycles of the customer use cases.

• Complete end-to-end test scenarios in different scopes: Regression, Performance, Functional and Scale; Report the progress of testing and provide summary reports of testing activity.

• Profiling, Benchmarking, and Analyzing Deep Learning models to identify areas for optimization and improvement in terms of performance, efficiency, and accuracy, with a strong emphasis on networking aspects.

• Providing insights and recommendations based on the analysis of large-scale training results, specifically focusing on networking bottlenecks and optimizations, to improve model outcomes and achieve business objectives.

What we need to see:

• B.A./B.Sc. in Computer Science or Electrical Engineering or equivalent experience as IT/Network Engineer.

• 6+ years of practical experience.

• Very Strong Hands-on experience in Linux based platform.

• Expertise in AI networking libraries (such as NCCL) and protocols (such as RoCE and RDMA).

• Ability to profile and optimize deep learning workflows, focusing on networking-related bottlenecks and optimizations, to improve overall performance and efficiency.

• Exceptional analytical and problem-solving skill, with a keen attention to detail, particularly in identifying and resolving networking performance issues.

• Fast and self-learner with outstanding technical skills.

• Independent, responsible worker, able to plan and complete.

• Standout colleague with good English communication and interpersonal skills.

• Scripts skills and experience: Bash / Python / Ansible

Ways to stand out from the crowd:

• Experience with virtualization technologies (KVM, HyperV, VMWARE, OpenStack, Kubernetes).

• Expertise in optimizing networking parameters, such as bandwidth, latency, or congestion control (such as DCQCN), for Deep Learning workloads.

• Familiarity with NVIDIA's networking technologies, such as Mellanox BF3, CX NIC, and their integration with Deep Learning workflows.

• Strong understanding of high-performance networking protocols and standards and their application to Deep Learning.