Senior HPC Engineer, GPU Compute

Nebius Group; Greater London; On-site; GBP 110,000 - 140,000; Full time

Benefits offered by this job

Competitive pay

Career growth

Flexible work

Collaborative culture

Impactful AI projects

International teams

Job summary

Nebius is building a cutting-edge hyperscaler platform and seeks a Senior HPC Cluster Engineer to optimize GPU computing, InfiniBand networks, and the KVM/QEMU stack in a high-performance cloud environment. You will work on hardware integration, performance tuning, and automation for reliability.

The role requires deep systems expertise, multi-GPU HPC experience, and strong programming skills in C/C++, Go, and Python, with a focus on scalable cloud infrastructure.

Qualifications

• 5+ years of professional experience in system-level software development focusing on performance optimization.
• 3+ years of hands-on Linux administration and performance tuning.
• Strong understanding of server architecture, PCIe devices, NICs, Linux OS/kernel, HPC systems.
• Proficiency in performance-oriented languages (C/C++, Go, Python).

Responsibilities

• Tune GPU clusters and InfiniBand networks for HPC performance.
• Analyze and troubleshoot root causes in GPUs and InfiniBand networks.
• Integrate new hardware into infrastructure, with Kubernetes, QEMU, and KVM support.
• Enhance automation for proactive monitoring and fault detection in GPU/InfiniBand environments.
• Configure and manage GPU devices and InfiniBand fabrics for reliability.

Skills

5+ years system-level software

3+ years Linux

C/C++

Go

Python

Job description

About Nebius:

Nebius is leading a new era in cloud infrastructure for the global AI economy. We are building a full-stack AI cloud platform that supports developers and enterprises from data and model training through to production deployment, without the cost and complexity of building large in-house AI/ML infrastructure.

Built by engineers, for engineers. From large-scale GPU orchestration to inference optimization, we own the hard problems across compute, storage, networking and applied AI.

Listed on Nasdaq (NBIS) and headquartered in Amsterdam, we have a global footprint with R&D hubs across Europe, the UK, North America and Israel. Our team of 1,500+ includes hundreds of engineers with deep expertise across hardware, software and AI R&D.

The role

We’re looking for aSenior HPC Cluster Engineerto join our team and play a key role in the development of our cutting-edge hyperscaler platform. TheGPU & InfiniBand teamis responsible for enhancing and optimizing the core components of our Cloud platform, with a specific focus onGPU computing,InfiniBand networks, and theKVM/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 toensure 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, includingsupport 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 insystem-level software development(focused on performance optimization, low-level programming).
• 3+ years of hands-on experience withLinux 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 moreperformance-oriented programming languages(C/C++, Go, Python).

It would be a plus if you have:

• Experience withGPU end-to-end testingin acluster environmentusing InfiniBand networking.
• Proven track record of analyzing and optimizing the performance ofHPC workloads(e.g., simulations, data analysis, AI/ML workloads).
• Familiarity withRDMA, RoCE, and InfiniBandprotocols for high-performance communication.
• Background inSoftware-Defined Networking(SDN) and experience withHPC cluster networking.
• Understanding ofQEMU/KVM virtualizationand managing virtualized environments.
• Experience withdeep learning frameworks such asPyTorchandTensorFlow, and their integration with HPC systems.
• Familiarity withcollective communication librarieslikeMPIandNCCLfor distributed computing.

We conduct coding interviews as part of the process.

Benefits & Perks:

• Competitive compensation
• Career growth and learning opportunities
• Flexibility and ownership
• Collaborative and innovative culture
• Opportunity to work on impactful AI projects
• International environment and talented teams

What's it like to work at Nebius:

Fast moving- Bold thinking- Constant growth- Meaningful impact- Trust and real ownership- Opportunity to shape the future of AI

Equal Opportunity Statement:

Nebius is an equal opportunity employer. We are committed to fostering an inclusive and diverse workplace and to providing equal employment opportunities in all aspects of employment. We do not discriminate on the basis of race, color, religion, sex (including pregnancy), national origin, ancestry, age, disability, genetic information, marital status, veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by applicable law.

Applicants must be authorized to work in the country in which they apply and will be required to provide proof of employment eligibility as a condition of hire.

If you need accommodations during the application process, please let us know.