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Graphcore

Delivers IPU-powered AI cloud services

Senior Software Engineer - ML QA

Test Automation EngineeringConfirmed live in the last 24 hours
Full-timeCambridge, UKNo salary listedRemote

About the Job

Requirements

  • Strong Python skills demonstrated through designing, developing, and maintaining production-quality software.
  • Software design and architecture skills for large, complex codebases, with a focus on testability and long-term maintainability.
  • Experience building continuous integration and continuous delivery pipelines and automated testing systems in Linux environments.
  • Familiarity with C or C++, including the ability to read, debug, and reason about low-level code.
  • Ability to mentor junior engineers and influence engineering practices through constructive feedback.
  • A self-directed approach to solving complex problems, identifying gaps, and driving improvements.
  • Applicants must have the legal right to work in the United Kingdom.

Responsibilities

  • Design production-quality test infrastructure that engineers can extend, maintain, and rely on as the machine learning software grows.
  • Architect scalable test frameworks and build continuous integration and continuous delivery pipelines that run across simulators, emulators, and physical hardware.
  • Create representative machine learning workloads, analyse their execution, and turn the results into practical improvements to testing and tooling.
  • Work across software teams, using code and design reviews to strengthen quality, security, and maintainability.
  • Use workload results to challenge assumptions and guide technical decisions about how the machine learning stack is tested.
  • Own improvements and act quickly on testing gaps.

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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