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Develops and optimises AI models for Graphcore’s advanced accelerator hardware, focusing on machine learning experiments, model performance, profiling and large-scale AI systems.
What you’ll work on
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.
Your team and support
The Applied AI team acts as a proxy for Graphcore’s customers. We understand current AI models, applications and software, then make sure Graphcore technology works at scale. You’ll work alongside people who write low-level kernels, train large language models and enjoy figuring out challenging AI problems together.
Work spans low-level kernel optimisation through to implementing research-level algorithms for new AI models. Engineers move between experiments, profiling, code reviews and technical debate – giving you a view of how different parts of an AI system fit together.
Decisions are driven by evidence, performance data and clear engineering judgement. 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.
How you’ll learn and grow
During the two-year programme, you’ll build technical range through hands-on work across AI models and accelerator systems.
With visibility across the full stack – from novel accelerator hardware and its software stack to state-of-the-art AI applications – you’ll identify opportunities to innovate and differentiate Graphcore’s technology.
What we’re looking for
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.
Benefits
Flexible working: Balance your work and personal life with greater flexibility
Retirement planning support: Up to 5% matched pension
Phantom equity: Share in Graphcore’s success
Workplace experience: Enjoy thoughtfully designed office spaces for collaboration, with free food and an on-site barista to support your day
Peace of mind protection: Income protection and life assurance to provide financial security for you and your loved ones
Electric Vehicle Scheme: Choose an electric vehicle and lease it through salary sacrifice
Flexible benefits: Tailor your benefits package with a choice of additional options, including private medical insurance and dental cover
Optional benefits: Dental cover, health cash plan, private medical insurance, cycle to work scheme, give as you earn
We welcome people from all backgrounds and experiences and are committed to building an inclusive environment where everyone can do their best work.
We’re an equal opportunity employer and recognise that everyone brings different strengths and perspectives. If you need any adjustments during the interview process, just let us know - we’re happy to support you.
Sponsorship
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.
Introduction to Graphcore
At Graphcore, we’re building next generation AI compute: from semiconductors and software to systems at datacenter scale. We are proud to be owned by SoftBank Group and work with other companies in the SoftBank family to deliver AI compute to customers working at the AI frontier.
Starting your career here means working alongside people with different backgrounds and expertise, from AI researchers to chip designers and software engineers. You’ll learn from each other, bring fresh ideas and help solve challenging problems together.
How to apply
Apply directly through the company website. Clicking the link below will open the application page in a new window.

Location: Bristol, UK
Industry: Digital & Technology
Graphcore has created a new processor, the Intelligence Processing Unit (IPU), specifically designed for artificial intelligence. The IPU’s unique architecture means developers can run current machine learning models orders of magnitude faster. More importantly, it lets AI researchers undertake entirely new types of work, not possible using current technologies, to drive the next great breakthroughs in general machine intelligence. Our next generation 3D Wafer-on-Wafer Bow IPU systems are helping AI innovators worldwide to build better, more innovative AI solutions, whether their focus is on language and vision, exploring graph neural networks and LSTMs or creating something entirely new. We believe our IPU technology will become the worldwide standard for artificial intelligence compute. The performance of Graphcore’s IPU is going to be transformative across all industries and sectors whether you are a medical researcher, roboticist or building autonomous cars. Our team is at the forefront of the artificial intelligence revolution, enabling innovators from all industries and sectors to expand human potential with technology. What we do, really makes a difference. We're always interested in hearing from exceptional people to join our team.
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