Offer summary

Qualifications:

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

Key responsibilities:

Tune the performance of GPU clusters and InfiniBand networks for HPC environments.

Analyze and troubleshoot issues related to GPUs and InfiniBand networks, proposing corrective actions.

Integrate new hardware into existing infrastructure, supporting GPU hardware through software stacks like Kubernetes, QEMU, and KVM.

Enhance automation systems for monitoring, detecting, and resolving issues in GPU and InfiniBand environments.

Job description

Why work at Nebius
Nebius is leading a new era in cloud computing to serve the global AI economy. We create the tools and resources our customers need to solve real-world challenges and transform industries, without massive infrastructure costs or the need to build large in-house AI/ML teams. Our employees work at the cutting edge of AI cloud infrastructure alongside some of the most experienced and innovative leaders and engineers in the field.

Where we work
Headquartered in Amsterdam and listed on Nasdaq, Nebius has a global footprint with R&D hubs across Europe, North America, and Israel. The team of over 800 employees includes more than 400 highly skilled engineers with deep expertise across hardware and software engineering, as well as an in-house AI R&D team.

The role

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.

What we offer

Competitive salary and comprehensive benefits package.
Opportunities for professional growth within Nebius.
Hybrid working arrangements.
A dynamic and collaborative work environment that values initiative and innovation.

We’re growing and expanding our products every day. If you’re up to the challenge and are excited about AI and ML as much as we are, join us!

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