Strategic Overview
System Engineer (Compute Node) at Nebius is defined by the responsibilities and candidate requirements in the employer's listing.
The published role emphasizes work such as 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.
The role is listed for Europe with a remote working arrangement, giving candidates the practical context needed to assess fit before applying.
Key information at a glance
About This Role
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.
Key Responsibilities & Objectives
- 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.
- 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.
Required Qualifications & Candidate Blueprint
- Experience with Kubernetes not only for deployment but for development is highly valued.
- Solid knowledge of internal OS architecture, performance considerations, process isolation and resource management.
- Knowledge of POSIX, sysfs, system calls, and file systems.
- Familiarity with server architecture, PCIe devices, NICs, and kernel drivers.
- Familiarity with the NVIDIA DOCA Software Framework will be an advantage.
- Knowledge of at least one of these languages, ready to learn or work with the others as needed.
Salary & Benefits
The available source data does not publish a numerical salary range for this opening. We do not estimate or substitute third-party figures.
- 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
Full Job Description
The following is the complete job description supplied by the source. We sanitize unsafe markup and remove external links, but do not shorten or rewrite the employer's source content.
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
The Compute Node team builds services for managing Virtual Machines running on GPU servers, integrating with disk management, virtual and InfiniBand networks. The team is also responsible for developing the Virtual Machine Scheduler that operates across clusters with thousands of servers and tens of thousands of GPUs, spanning multiple data centers in several regions.
We expect you to have:
1. Containerization & Orchestration
Experience with Kubernetes not only for deployment but for development is highly valued.
2. Virtualization
KubeVirt and QEMU/KVM familiarity is a high plus.
3. Linux & System-level Understanding
Solid knowledge of internal OS architecture, performance considerations, process isolation and resource management.
Knowledge of POSIX, sysfs, system calls, and file systems.
Familiarity with server architecture, PCIe devices, NICs, and kernel drivers.
4. Hardware Acceleration
Experience or strong interest in working with GPUs, DPUs, or ARM architectures is desirable.
Familiarity with the NVIDIA DOCA Software Framework will be an advantage.
5. Go, C++ Proficiency
Knowledge of at least one of these languages, ready to learn or work with the others as needed.
Strong grasp of concurrency, debugging, and profiling techniques.
We conduct coding interviews as part of the process.
#LI-JS1
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.
Editor’s Market Perspective (Our Custom Analysis)
Why This Position Matters
This opening may suit candidates who can demonstrate experience relevant to the employer's published requirements. Its strongest career signal is the scope of the work itself — particularly 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. — rather than a generic title alone.
Resume & Application Strategy
For the application, connect specific examples from your experience to the responsibilities and qualifications in the employer's description. Quantify outcomes from comparable work, and place the most relevant evidence near the top of the resume. When the employer explicitly names tools, platforms, leadership scope, or domain experience, use those source terms accurately and in context.
We organize source-provided information into this independent job-seeker overview. Compensation is shown only when the source provides it; the official listing remains the authority for current requirements and application instructions.