HPC Cluster Engineer

We’re looking for a Senior HPC Cluster Engineer to join our team and play a key role in the development of our cutting-edge hyperscaler platform. The GPU & InfiniBand team is responsible for enhancing and optimizing the core components of our Cloud platform, with a specific focus on GPU computing, InfiniBand networks, and the KVM/QEMU stack. You’ll work closely with hardware virtualization and device emulation technologies, ensuring high performance and security in multi-GPU, HPC environments. The role involves analyzing, troubleshooting, and improving infrastructure to support new hardware, fine-tuning system performance, and automating fault detection and resolution in a complex system. In this position, you will be responsible for: - Tuning the performance of GPU clusters and InfiniBand networks to ensure optimal operation in HPC and GPU-based environments. - Analyzing and troubleshooting the root cause of issues related to GPUs and InfiniBand networks, and proposing corrective actions. - Integrating new hardware into the existing infrastructure, including support for new GPU hardware through software stacks like Kubernetes, QEMU, and KVM. - Enhancing automation systems for proactive monitoring, detecting, and resolving issues in GPU and InfiniBand environments. - Configuring and managing GPU devices and InfiniBand fabrics, ensuring efficient and reliable operation. We expect you to have: - 5+ years of professional experience in system-level software development (focused on performance optimization, low-level programming). - 3+ years of hands-on experience with Linux systems (administration, troubleshooting, and performance tuning). - In-depth understanding of server architecture, including PCIe devices, NICs, Linux OS/Kernel, and high-performance computing (HPC) systems. - Strong proficiency in one or more performance-oriented programming languages (C/C++, Go, Python). It would be a plus if you have: - Experience with GPU end-to-end testing in a cluster environment using InfiniBand networking. - Proven track record of analyzing and optimizing the performance of HPC workloads (e.g., simulations, data analysis, AI/ML workloads). - Familiarity with RDMA, RoCE, and InfiniBand protocols for high-performance communication. - Background in Software-Defined Networking (SDN) and experience with HPC cluster networking. - Understanding of QEMU/KVM virtualization and managing virtualized environments. - Experience with deep learning frameworks such as PyTorch and TensorFlow, and their integration with HPC systems. - Familiarity with collective communication libraries like MPI and NCCL for distributed computing. We conduct coding interviews as part of the process.

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