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Graphcore

Delivers IPU-powered AI cloud services

Staff Hardware Engineer

Hardware Validation & Testing +1Confirmed live in the last 24 hours
Full-timeBristol, UKNo salary listedIn-person

About the Job

Requirements

  • Strong knowledge of server hardware architectures and board-level debugging.
  • Experience isolating failures using system logs, telemetry, power data, and thermal metrics.
  • Hands-on experience with high-performance computing systems, artificial intelligence compute platforms, or rack-scale infrastructure.
  • Ability to lead structured root-cause analysis and propose practical corrective actions.
  • Confidence working across engineering, platform, and data centre teams.
  • Clear written and verbal communication, with the judgement to guide junior engineers.
  • Legal right to work in the United Kingdom.

Responsibilities

  • Lead advanced operational, diagnostic, and engineering support across laboratory and data centre environments.
  • Improve hardware bring-up, validation, and troubleshooting for artificial intelligence compute platforms.
  • Diagnose failures across server blades, racks, power systems, thermal behaviour, network configuration, and BIOS/baseboard management controller issues.
  • Turn complex problems into clear root-cause analysis, corrective action, and improved operating practices.
  • Support new platforms from early bring-up through deployment.
  • Guide others, improve documentation, and help raise the standard of hardware diagnostics.

About the Company

Graphcore

Delivers IPU-powered AI cloud services

Graphcore.ai focuses on building and delivering Intelligence Processing Units (IPUs) and related AI services for enterprises. It provides IPU-powered cloud services, pre-trained AI models, optimized inference engines, and APIs on a subscription basis with on-demand pricing and free tiers through cloud partners. The IPUs accelerate AI workloads and enable scalable, cost-efficient AI deployment in enterprise applications. The company differentiates itself through specialized IPU hardware and optimized software stack, plus partnerships with cloud providers to reach customers, rather than relying on generic hardware. The goal is to help businesses scale AI-powered products and operations efficiently by offering flexible, scalable compute and ready-to-use AI components.

Company size
501-1,000
Company stage
Growth Equity (Non-Venture Capital)
Total funding
$1.1B
Headquarters
Bristol, United Kingdom
Founded
2016

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