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Graphcore

Delivers IPU-powered AI cloud services

Graduate Engineer - System Validation

Hardware Validation & TestingConfirmed live in the last 24 hours
Full-timeAustin, TX, USANo salary listedIn-person

About the Job

Requirements

  • Working toward a Bachelor's or Master's degree in Computer Engineering, Electrical Engineering, or a related field, with a clear path to graduation.
  • Exposure to hardware validation or debugging based on x86- or ARM-architecture server systems, racks, or embedded systems.
  • Understanding of key concepts related to CPU/GPU, memory, I/O, and BIOS testing.
  • Experience with Linux/server operating systems and automation using Python or Bash.
  • Experience with CI/CD pipelines and large-scale test automation infrastructure.
  • Experience working in laboratory environments.

Responsibilities

  • Help drive and execute post-silicon validation goals for AI compute blades and racks, including test-case planning, development, and automation.
  • Help drive validation test-case execution and system debugging against program milestones, and report validation progress and risks.
  • Drive provisioning and integration of system components (SoC firmware, BMC, RMC, and operating system) for rack-level readiness.
  • Triage test failures, collect debugging data, and collaborate on root-cause analysis.
  • Track validation coverage and continuously improve test processes and infrastructure.

Desired Qualifications

  • Knowledge of BMC, IPMI, and Redfish concepts.
  • Familiarity with OpenBMC and processes for verifying firmware functionality.
  • Experience with test and asset management tools.

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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