> Markdown version of [/jobs/ext/3838162-graduate-machine-learning-engineer-2027](https://www.wearedevelopers.com/jobs/ext/3838162-graduate-machine-learning-engineer-2027). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Graduate Machine Learning Engineer 2027 - **Company:** Graphcore - **Location:** Bristol, UK - **Experience:** Starter - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Machine Learning, Software Engineering, Pytorch, Deep Learning, Information Technology - **Published:** October 20, 2026 - **Apply:** https://job-boards.greenhouse.io/graphcore/jobs/8894041002 ## About the Role * Bachelor/Master's degree in Machine Learning, Computer Science, Maths, Data Science, or related field * Software development skills and proficiency with a deep learning framework such as PyTorch or JAX * An understanding of deep learning architectures, optimisation, evaluation and scaling, with the ability to design, run and explain ML experiments * A collaborative approach and willingness to work through unfamiliar technical problems, ask questions and take responsibility You can demonstrate these skills through coursework, a dissertation, personal or team projects, research, or other relevant experience. Tell us what you built or investigated, how you approached it and what you learned., Applicants must already have the right to work in the UK for the full duration of the programme, without requiring visa sponsorship. We are unable to sponsor work visas for our Early Careers opportunities. ## Description Turn the models you've studied into AI systems that run at scale. In Applied AI, you'll help implement, train and optimise advanced models on Graphcore's next generation hardware, connecting research ideas with systems running across thousands of accelerators. You'll benchmark models, use profiling to find performance bottlenecks, design experiments and contribute fixes across models, software and accelerator systems. Working with Research, Software and Product teams, you'll test ideas that could inform future hardware. Your experiments will help us understand what makes a model accurate, efficient and ready to scale.