Build and scale faster on the purpose-built AI cloud, engineered from silicon to API. Backed by Accel.
About the role
We’re looking for a Network Software Engineer (NetSWE) to build software that makes network operations safe, scalable, and boring — even as we launch new data centers and expand fast. This is not a “write scripts for configs” role: you’ll build the tooling and services that sit between the network core (switches/ports/VLANs, traffic processors) and the cloud platform on top, using open source where it fits and building the missing pieces where it doesn’t.
What they're looking for
- Background in networking (ex-network engineer, CCNP/education, DC networking exposure) or strong interest and proven ability to learn fast
- Experience building automation/infra tooling: CI/CD, IaC, testing/staging environments, or “network-as-code” style workflows
- Low-level networking / datapath experience: eBPF/XDP, DPDK, kernel networking, traffic processing systems
- Experience designing high-load services and observability platforms (metrics/logs/traces, alerting, regression detection)
- Contributions to open source or experience extending/debugging OSS components in production environments
More about this role
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.
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,...
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