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Open nowPosted 4 hours ago

Network Infrastructure Engineer

CommonAI C.I.C.

Where
Cambridge, England, United Kingdom
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Your applicationOpen nowNetwork Infrastructure EngineerCommonAI C.I.C. · Cambridge, England, United Kingdom

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This job: posted 4 hours ago

The posting

The Opportunity

Design, build and keep evolving the physical networks that connect the clusters in the Scaling Inference Lab (SIL). The SIL, backed by ARIA, is a neutral, UK-based testbed where new AI technologies (accelerators, memory systems and interconnects) are tested at rack scale against real workloads for the very first time. The results help UK startups, investors and public compute programmes decide what to build, fund and buy, and they build lasting UK capability in the infrastructure that AI depends on

The network is critical to every experiment and this role will own the cabling, switch layouts and topologies for the out-of-band, frontend and accelerator fabrics in our lab at Kao Data in Harlow, and in any further facilities we establish in the UK.

The SIL is an R&D facility and its requirements evolve rapidly. A new cluster might need a rail-optimised InfiniBand fabric, an 800G Ethernet frontend or an optical circuit-switched interconnect that has never been deployed at this scale. An older cluster might need re-cabling so its equipment can be reused in the next one. You will gather requirements from members, CommonAI staff and other key stakeholders to create flexible and resilient network designs.

In this role you will work closely with both technical staff and the project management team to provide the detailed designs that suppliers, cabling contractors and installers need.

What you will do

  • Design the physical network for each new cluster across out-of-band, frontend/storage and accelerator fabrics: topology, switch placement, port maps, cable schedules and bills of materials.
  • Specify fibre and copper infrastructure in detail, including fibre grade, connectors, polarity, pinning, trunk and cassette layouts, patch-panel arrangements and end-to-end loss budgets, and select matching transceivers, DACs and AOCs.
  • Plan changes to existing clusters so equipment can be re-cabled and reused with minimal disruption to running work.
  • Act as the technical authority for suppliers and installers: produce drawings and specifications, review quotations, and inspect and test completed work.
  • Maintain accurate, well-labelled as-built documentation of every rack, cable, port and link.
  • Work with project managers on sequencing and lead times, and with operators and software colleagues on bring-up and fault-finding.

An example early project would be to produce the complete network design for an upcoming cluster, oversee its installation, test the links and hand over as-built documentation to the operations team.

Requirements

  • Experience designing networks for HPC or AI cluster deployments, with examples of designs you have owned from specification to installation.
  • A thorough understanding of the differences between out-of-band, frontend and accelerator (GPU) fabric networking.
  • Practical knowledge of InfiniBand, RoCE or similar lossless fabrics, including fat-tree and rail-optimised topologies.
  • A very clear understanding of data centre fibre optics: OS2 versus OM4/OM5, MTP/MPO versus LC, APC versus UPC, Type A/B/C polarity, pinned and unpinned connectors, and the losses introduced by patch panels, cassettes and connectors.
  • The ability to communicate a design clearly to installers, suppliers, project managers and engineers.

Experience with 400G/800G Ethernet and OSFP/QSFP-DD optics, optical circuit switching or other novel interconnects, high-density liquid- or air-cooled racks, documentation tools such as NetBox, and colocation facilities would be useful. Depth in a subset is sufficient; the lab will keep presenting new requirements and we expect you to learn alongside us.

Benefits

  • A collaborative and supportive work environment
  • The opportunity to have a high impact in a growing organisation
  • Competitive salary package, including pension and benefits
  • Professional development opportunities
  • Networking opportunities with influential figures from across the tech sector and academia
  • A vibrant office environment located a few minutes' walk away from Cambridge train station

Working with us

This role is based in our Cambridge office with occasional travel to our lab in Kao Data, Harlow, particularly during builds and changes. Occasional travel to future sites elsewhere in the UK will be part of the role. Support is generally only required during UK business hours, although major installation work may occasionally be scheduled for evenings or weekends.

We are open to permanent, part-time or consultancy arrangements and would like you to start as soon as practical. While our preference is for staff to be based in our Cambridge office we will consider hybrid and fully remote applicants. We particularly welcome experienced engineers but will also consider earlier-career candidates with strong evidence of ability. Qualifications and vendor certifications are useful but secondary to experience and the quality of your work.

CommonAI CIC is an equal opportunity employer and is committed to creating an inclusive and diverse workplace.

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