Magnet.me  -  Het slimme netwerk waar studenten en professionals hun stage of baan vinden.

Het slimme netwerk waar studenten en professionals hun stage of baan vinden.

Senior Site Reliability Engineer (SRE, Compute Node Team)

Geplaatst 16 okt. 2026
Delen:
Werkervaring
5 tot 10 jaar
Full-time / part-time
Full-time
Functie
Opleidingsniveau
Taalvereiste
Engels (Vloeiend)

Bouw aan je carrière op Magnet.me

Maak een profiel aan en ontvang slimme aanbevelingen op basis van je gelikete vacatures.

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.

The Role

We are looking for a Senior Site Reliability Engineer (SRE) to join the Compute Node team at Nebius AI Cloud. The Compute Node team is responsible for building and operating the cluster scheduler and node-level services that run and manage virtual machines across all cloud regions. This role focuses on Linux systems engineering, virtualization and operational reliability. You will work close to the operating system and hypervisor, shaping how reliability and observability are embedded into the Compute platform.

  • Amsterdam, Netherlands; Remote - Europe

Your responsibilities will include:

  • Ensure reliability, availability and performance of compute nodes running VMs
  • Analyze and debug Linux systems across user space and kernel space, understanding capabilities, limitations and trade-offs at each layer
  • Troubleshoot complex production issues involving CPU, memory, NUMA, cgroups and scheduling
  • Work hands-on with virtualization and containerization, primarily using QEMU/KVM and Linux-native technologies
  • Design and evolve observability as a core capability of the node layer: metrics, logs, traces, alerts, SLIs and SLOs
  • Lead incident response, root-cause analysis, and postmortems, driving long-term reliability improvements
  • Collaborate closely with platform, kernel/hypervisor, GPU and infrastructure teams to improve system design and operability

We expect you to have:

Strong Linux expertise:

  • deep understanding of Linux user space and kernel space
  • knowledge of kernel subsystems (scheduler, memory management, filesystems, cgroups, namespaces)
  • clear understanding of system boundaries and constraints at different layers

Virtualization experience:

  • hands-on experience with QEMU/KVM
  • understanding of VM lifecycle, performance characteristics and failure modes

Containerization knowledge:

  • practical experience with containers, namespaces and cgroups
  • strong understanding of resource isolation and control

Strong debugging skills:

  • ability to reason about complex system failures
  • structured, hypothesis-driven approach to incident analysis

SRE mindset:

  • clear understanding of the SRE role in system design and operations
  • experience building and operating observability stacks, not just consuming them
  • ability to turn system behavior into actionable reliability signals

Nice to Have / Optional:

  • Experience with Kubernetes internals or node-level components
  • Hands-on experience with low-level Linux debugging tools (e.g. perf, eBPF, ftrace, strace, kernel crash dumps)
  • Familiarity with large-scale compute or bare-metal platforms
  • Contributions to open-source infrastructure or system software
  • Experience debugging hardware and driver-level issues, including GPUs, NVLink, InfiniBand

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

Nebius provides AI cloud infrastructure, offering a full-stack cloud platform for AI developers, enterprises, and research institutes to build and deploy generative AI applications and train and run machine learning models in a secure, high-performance, and cost-optimized environment.

ICT
Amsterdam
1.782 medewerkers