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Graphcore is seeking a Software Engineer to join the Frameworks team and build critical framework support that helps AI developers unlock Graphcore hardware. You will work on integrating Graphcore accelerators with state-of-the-art ML frameworks, including Triton and PyTorch, reporting to a Team Lead in Frameworks.
In this role, you will design, implement, optimize, and support software that shapes how researchers and engineers use Graphcore hardware for demanding machine learning workloads. You will improve performance, quality, and usability across a complex software stack. Your responsibilities include delivering new features, reviewing code, writing technical documentation, and working with upstream open-source communities. You will also help coordinate open-ended technical work across teams.
The Frameworks team connects Graphcore hardware with the tools ML engineers and researchers rely on, working across PyTorch, Triton, JAX, and TensorFlow with a focus on usability and performance. Work happens through agile practices, close technical discussion, and clear ownership. Engineers are trusted to speak up, solve hard problems, and move work forward with pace. Decisions are shaped by evidence, code quality, and business outcomes.
This role offers deep technical ownership and visible impact as the ML software landscape evolves. You will keep learning and may contribute across other framework teams, working both within Graphcore and with open-source communities to deliver software developers can trust.
Graphcore is one of the world's leading innovators in AI compute, developing hardware, software, and systems infrastructure for next-generation AI breakthroughs. As part of the SoftBank Group, Graphcore is positioned to shape the future of AI infrastructure.
REQUIREMENTS:
· Strong software engineering skills with judgment to manage quality, complexity, and technical debt
· Experience developing in Python and C++
· Experience in compiler development
· Ability to manage complex technical tasks with cross-team dependencies
· Clear communication skills with a proactive approach to collaboration and technical leadership
· Interest in AI, ML frameworks, performance optimization, or computationally intensive engineering
