Nebius

Senior Systems Software Engineer, GPU Compute

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SeniorZdalnie·LondynFull-time

#467514·Dodano 7 miesięcy temu·0

Źródło: Nebius

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Tech Stack / Keywords

GPUInfiniBandLinux C/C++Go Python KubernetesQEMUKVMHPC

Podsumowanie oferty

Join the GPU & InfiniBand team developing Nebius’s hyperscaler cloud platform. You’ll optimize and troubleshoot GPU computing and InfiniBand infrastructure, integrate new hardware, and improve automation across HPC environments using technologies including Kubernetes, QEMU, and KVM.

Wymagania

5+ years of professional experience in system-level software development, focused on performance optimization and low-level programming.
3+ years of hands-on experience with Linux systems, including administration, troubleshooting, and performance tuning.
In-depth understanding of server architecture, including PCIe devices, NICs, Linux OS/Kernel, and HPC systems.
Strong proficiency in one or more performance-oriented programming languages: C/C++, Go, or Python.

Nice to 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, such as simulations, data analysis, and 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.

Obowiązki

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.

Benefity

Career growth and learning opportunities.

Udziały pracownicze

Inne informacje

Applicants must be authorized to work in the country in which they apply and provide proof of employment eligibility as a condition of hire.
The recruitment process includes coding interviews.

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