Graphcore is one of the world’s leading innovators in Artificial Intelligence compute. It is developing hardware, software and systems infrastructure that will unlock the next generation of AI breakthroughs and power the widespread adoption of AI solutions across every industry.
As part of the SoftBank Group, Graphcore is a member of an elite family of companies responsible for some of the world’s most transformative technologies. Together, they share a bold vision: to enable Artificial Super Intelligence and ensure its benefits are accessible to everyone.
Graphcore’s teams are drawn from diverse backgrounds and bring a broad range of skills and perspectives. A melting pot of AI research specialists, silicon designers, software engineers and systems architects, Graphcore enjoys a culture of continuous learning and constant innovation.
Build the software that helps machine learning developers get more from Graphcore hardware. As a Graduate Software Engineer in our Triton team, you will help connect Graphcore accelerators with the ML frameworks developers use every day.
Your work will make our software easier to use, more reliable and more performant for real AI workloads. You will learn how compilers, frameworks and hardware interact in a production engineering setting.
You will contribute to features, tests, documentation, code reviews and performance improvements across a complex codebase. You will be supported by experienced engineers while taking ownership of meaningful work early.
This role suits a curious graduate who wants to grow deep technical skills and see their code make a practical difference.
The Frameworks team makes Graphcore hardware work smoothly with tools such as PyTorch, Triton, JAX and TensorFlow. The team sits close to compilers, runtime software and hardware, so you will learn from different technical perspectives.
Work is organised through SCRUM, with clear priorities, regular feedback and shared accountability. You will own well-scoped tasks, ask questions early and build confidence through reviews, testing and documentation.
Decisions are shaped by technical evidence, user impact and open discussion. Engineers are expected to speak up, challenge assumptions and improve how the team works.
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