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Graphcore

Delivers IPU-powered AI cloud services

Graduate Software Engineer - Accelerator Modelling

Software EngineeringConfirmed live in the last 24 hours
Full-timeBristol, UK£45k /yr

About the Job

Requirements

  • A Bachelor's or Master's degree, or equivalent experience, in Computer Science, Maths, Machine Learning, Data Science or a related field.
  • Strong C++ programming skills gained through study, projects, personal coding or practical experience.
  • An understanding of computer science fundamentals and an interest in lower-level software.
  • The ability to debug complex problems and explain your thinking clearly, with exposure to debugging tools, performance analysis, testing, version control or collaborative software development practices.
  • Curiosity about processor architecture, hardware simulation, performance modelling or systems behaviour, and willingness to ask questions and learn through feedback.

Responsibilities

  • Develop, test and refine models and simulations for next-generation AI accelerators to predict performance, power consumption and scalability, helping engineers compare approaches before hardware decisions are made.
  • Investigate how complex workloads behave, and contribute to planning, design, implementation and testing.
  • Help other teams integrate future hardware versions and help scale distributed modelling environments.
  • Develop and debug modelling code to understand complex workload behaviour and test whether a model captures that behaviour.
  • Work with architects, engineers and machine learning researchers to understand how modelling results inform hardware decisions and connect to the wider computing system.

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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