• Join Graphcore in a permanent role and start your career with two years of hands-on learning. From day one, you’ll be trusted to take ownership, share your ideas and help shape what we’re creating
• You’ll tackle challenging problems alongside a team who support your development and are as excited about your success as you are
• 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
• 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
• 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

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

• 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
• Software development skills and proficiency with a deep learning framework such as PyTorch or JAX
• Bachelor/Master’s degree in Machine Learning, Computer Science, Maths, Data Science, or related field

• Start date: September 2027
• Application deadline: Midnight, 29th November 2026
• We encourage you to apply early, as we may close applications before the advertised deadline
• To apply, answer the application questions below and upload your CV and cover letter. We’ll let you know the outcome of your application by early December at the latest. If successful, you’ll be invited to complete a technical assessment
• Candidates who reach the final stage will then be invited to attend in-person assessments in early spring