Senior Site Reliability Engineer (SRE, Compute Node Team)
Level inferred from job title
Job description
Senior Site Reliability Engineer on the Compute Node team at Nebius AI Cloud, building and operating the cluster scheduler and node-level services that run and manage virtual machines across all cloud regions. The role focuses on Linux systems engineering, virtualization and operational reliability close to the OS and hypervisor.
At a glance
- Work mode
- Remote
What you'll do
- 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
What we're looking for
- 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
- 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
Your team
Compute Node team
Responsible for building and operating the cluster scheduler and node-level services that run and manage virtual machines across all cloud regions.
Benefits
- 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
Apply
About Nebius
Leading a new era in cloud infrastructure for the global AI economy
Nebius is building a full-stack AI cloud platform. Built by engineers, for engineers, from large-scale GPU orchestration to inference optimization, owning the hard problems across compute, storage, networking and applied AI. Listed on Nasdaq (NBIS) and headquartered in Amsterdam, with a global footprint and R&D hubs across Europe, the UK, North America and Israel.
Mission
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.
Key facts
- 1,500+
- Amsterdam
- AI cloud infrastructure
- Listed on Nasdaq (NBIS)
- Global footprint with R&D hubs across Europe, the UK, North America and Israel
- Team of 1,500+ includes hundreds of engineers with deep expertise across hardware, software and AI R&D
What they value
- Fast moving
- Bold thinking
- Constant growth
- Meaningful impact
- Trust and real ownership
- Opportunity to shape the future of AI