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Nebius

GPU Cluster Architect

India +1

Location
India · Singapore
Work
Not stated
Employment
Not stated
Level
Lead / staff
Function
Engineering
Pay
Not stated
Posted
3 months ago

About the 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.

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

We are seeking a GPU Cluster Architect to drive the design of our next-generation AI infrastructure. In this high-impact, hands-on role, you will make end-to-end architectural decisions across compute, networking, and storage — ensuring our platforms can meet the massive scale, performance, and reliability requirements of modern AI workloads.

This is a high-impact, hands-on architecture role where you’ll define how tens of thousands of GPUs are interconnected, cooled down, powered, and optimized across multiple data center sites.

Your responsibilities will include

  • Cluster Design: Architect scalable GPU cluster topologies including compute nodes, interconnect (InfiniBand, Ethernet), storage, and control planes.
  • Performance Modeling: Analyze AI/ML workloads (e.g. LLM training, inference) to inform design tradeoffs across latency, bandwidth, and GPU density.
  • Network Architecture: Align with network architect relevant design and validate low-latency, high-throughput interconnects (e.g., InfiniBand HDR/NDR, RoCEv2) at POD and DC scale.
  • Storage Integration: Work with storage teams to optimize performance for training datasets, checkpointing, and others.
  • Reliability & Monitoring: Understand and analyze signal from monitoring systems to the detect flows in design
  • Collaboration: Partner with site reliability, networking, storage, and DC engineering teams to operationalize and scale your architecture.

We expect you to have

  • 5+ years of experience designing clusters.
  • Deep understanding of modern GPU architecture (NVIDIA, AMD, etc.).
  • Experience with HPC interconnects (InfiniBand & RoCE).
  • Solid background in systems architecture, networking, and hardware reliability.
  • Experience in scripting for automation and telemetry pipelines (Python, Go, etc.)

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.

Source

Posted by Nebius on their own hiring page, careers.nebius.com. OptiTalent shows it as published, read 07 Nov 2026 01:34 UTC; the original is the reference.

View the original ad ↗

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