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Graphcore

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Graduate Software Engineer (Frameworks 2027)

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Summary

A two-year graduate programme in Bristol where you’ll build software connecting Graphcore’s ML accelerators with PyTorch and Triton, implementing features, optimising performance, fixing defects, and writing tests and documentation while learning about compilers and runtime software for AI workloads.

  • As a Graduate Software Engineer across our Frameworks team, you’ll develop software connecting Graphcore’s machine learning accelerators with frameworks including PyTorch and Triton. You’ll implement features, optimise performance, resolve defects and create tests and technical documentation. You’ll write and improve tests, investigate issues and help make the software more reliable and faster
  • You’ll also write clear documentation and take part in code reviews, discussing ideas and learning from feedback. Take ownership of clearly scoped tasks, with support from experienced colleagues as you learn your way around the codebase
  • The Frameworks team works with tools including PyTorch and Triton Its work connects these tools with compilers, which translate code for hardware, and runtime software, which helps it execute
  • We plan and review work in short cycles using Scrum. You’ll have clear priorities, regular feedback and opportunities to learn from colleagues working across software and hardware. Technical evidence and the needs of our users help guide our decisions
  • You’ll be encouraged to ask questions, challenge existing approaches and share ideas for making things better. Take responsibility for your work and speak up when you spot a problem or need support
  • During the two-year programme, you’ll build your understanding of how software and hardware work together to run AI workloads
  • Hands-on tasks will help you develop your knowledge of compilers and runtime software, alongside your skills in testing, debugging and documentation. Code reviews and technical discussions will give you feedback on your approach and help you learn how other engineers solve problems
  • As you build confidence in the codebase, you’ll learn how to turn an idea into a software feature, investigate how it behaves and explain your work to colleagues

Benefits

  • Work-Life Balance: We believe you should have a good work-life balance. Everyone’s situation is different, so we offer flexible working arrangements and start and finish times, allowing you to choose when to work from home or come into the office
  • Healthcare: We offer Private Medical Insurance (PMI) to our employees to help them take care of their health and that of their loved ones
  • Pension: We believe that our employees deserve the best when it comes to planning for their future
  • Income Protection: Graphcore understands that unforeseen circumstances can happen, and we want to ensure our employees have the necessary financial security in place
  • Progression: We prioritise learning and development as an integral part of our culture at Graphcore. Our Talent Development team is dedicated to equipping all our employees with the necessary tools, resources, and support to enhance their skills and reach their full potential in their careers
  • Wellbeing: We want to ensure that our employees have the resources and support they need to prioritise their health and wellbeing
  • You can demonstrate these skills through coursework, a dissertation, personal or team projects, placements, internships, open-source contributions or other relevant experience
  • Practical experience or a strong academic understanding of compiler development, ML frameworks or a computationally intensive engineering field
  • Relevant modules and university projects count as evidence of your compiler knowledge. Tell us what you built or investigated, how you approached it and what you learned
  • Bachelor’s/Master’s degree in Computer Science, Maths, Machine Learning, Data Science or a related field
  • Hands-on experience with Python or C++, with the ability to write clear, maintainable code, tests and documentation
  • An interest in AI, machine learning frameworks, high-performance software or computer architecture, with curiosity and openness to learning through feedback and technical discussions
  • Start date: September 2027
  • Application deadline: Midnight, 29th November 2026

Skills

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