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Graphcore

Delivers IPU-powered AI cloud services

Manufacturing Operations Intern - Product Test

Hardware Validation & TestingConfirmed live in the last 24 hours
Internship · Summer 2027Bristol, UK£14.42 /hrIn-person

About the Job

Requirements

  • Currently studying for a bachelor's or master's degree in Mechanical, Electrical or Electronic Engineering, Physics, Computer Science or a related field, or equivalent experience.
  • An understanding of electronics or printed circuit board fundamentals, with an interest in semiconductor technology, manufacturing, test or validation.
  • Programming or scripting experience, ideally with Python.
  • The ability to use data to investigate problems and communicate findings, demonstrated through practical work involving electronics, embedded systems, validation, or automation.

Responsibilities

  • Contribute to practical work testing, diagnosing and improving advanced artificial intelligence hardware across silicon, boards, server blades or rack-scale systems.
  • Depending on the project, develop automated test solutions, run system-level tests and analyse the results.
  • Work on a defined project or set of activities that helps improve how products are tested and understood.
  • Run tests, analyse data and investigate issues in order to connect studies with real hardware and explain findings.

Desired Qualifications

  • Familiarity with Linux, Bash or Git.

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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