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Technical Program Manager - Compute Systems Engineering

NebiusNetherlands, United Kingdom🌍 Remote
Full-timeSenior
👁️ 0 views📝 0 applicationsPosted 7/30/2026Expires 9/28/2026
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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. About the team The Compute Systems Engineering organization owns the full systems stack behind Nebius HPC and GPU Cloud deployments.

We develop and operate the core components of our virtualization platform— including the Linux kernel, KVM, QEMU, device drivers, and firmware — together with ultra-high-bandwidth, HPC-grade networking, state-of-the-art NVIDIA GPUs, and other cutting-edge hardware.

In less than two years, we have brought up and successfully operated large-scale B300 and H200 GPU clusters for Cloud customers. These deployments comprise tens of thousands of GPUs across multiple data centers in US, UK, France, and other European countries – with hundreds of thousands more GPUs expected to follow.

One of our most significant challenges is continuing to evolve and scale the Nebius Compute platform to support NVIDIA’s flagship GB300 systems and upcoming VR200 solutions. Our organization is responsible for: Regularly adapting our systems stack to support the latest hardware platforms and technologies.

Developing and maintaining performance improvements and customer-facing capabilities – based on both business requirements and engineering needs. Building and operating reliable, comprehensive deployment automation and vali

Required Skills

LinuxMachine Learning

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