Graduate Software Engineer, Accelerator Modelling 2027

Graphcore; West of England; On-site; GBP 34,000 - 42,000; Full time

Benefits offered by this job

Flexible working

Retirement planning (pension)

Phantom equity

On-site food and beverages

Income protection and life assurance

EV salary sacrifice

Flexible benefits (private medical,;d)

Dental cover

Cycle to work

Job summary

Graphcore in Bristol, UK, invites applications for the Graduate Software Engineer, Accelerator Modelling 2027. This two-year programme develops your C++ modelling, software and hardware simulation skills, tackling performance, power and scalability questions for future AI accelerators.

You’ll work closely with the Accelerator Modelling Team across architecture, hardware and software, with buddy support and a strong emphasis on hands-on learning and engineering judgement.

Qualifications

• Bachelor’s/ Master’s degree, or equivalent experience, in Computer Science, Maths, Machine Learning, Data Science or a related field
• Strong C++ programming skills, gained through study, projects, personal coding or practical experience
• An understanding of computer science fundamentals and an interest in lower‑level software
• The ability to debug complex problems and explain your thinking clearly, with exposure to debugging tools, performance analysis, testing, version control or collaborative software development practices
• Curiosity about processor architecture, hardware simulation, performance modelling or systems behaviour, and a willingness to ask questions and learn through feedback
• 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.

Responsibilities

• Develop, test and refine models and simulations for the next-generation AI accelerators.
• Your work will help predict performance, power consumption and scalability, giving engineers evidence to compare approaches before hardware decisions are made.
• Investigate how complex workloads behave, contribute to planning, design, implementation and testing, and help other teams integrate future hardware versions.
• Help scale distributed modelling environments and see how software models connect architectural ideas with future hardware.
• Collaborate with architects, engineers and machine learning researchers to ensure modeling results inform hardware decisions.

Skills

C++ programming

CS fundamentals

Debugging complex problems

Processor architecture curiosity

Education

Bachelor’s/Master’s degree or equivalent in CS/Maths/ML/DS

Tools

Version control (Git)

Job description

Graduate Software Engineer, Accelerator Modelling 2027

Bristol, UK

Location: Bristol, UK
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.

The Graduate Programme at Graphcore

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.

Put your C++ skills to work modelling future AI accelerators before they exist and help shape how Graphcore engineers design them.

As a Graduate Software Engineer in Accelerator Modelling, you’ll develop, test and refine models and simulations for the next-generation AI accelerators. Your work will help predict performance, power consumption and scalability, giving engineers evidence to compare approaches before hardware decisions are made.

You’ll investigate how complex workloads behave, contribute to planning, design, implementation and testing, and help other teams integrate future hardware versions. You’ll also help scale distributed modelling environments. It’s a chance to see how software models connect architectural ideas with future hardware.

Your team and Support

The Accelerator Modelling Team works across architecture, hardware and software.

You’ll be working in a small team, team lead and all senior members would support you with every step on your way. Modelling team faces a lot of the unknowns and challenging problems at the cutting edge of AI technology. There’s a buddy system in place, so you will always have a point of contact , ready to answer all questions or help with anything.

Decisions are driven by evidence from the models and clear engineering judgement. You’ll be encouraged to ask questions, challenge existing approaches and share ideas for making things better.

How you’ll learn and grow

During the two-year programme, you’ll build practical experience in C++ development, hardware simulation and performance modelling, building skills close to architecture, software and hardware design.

Developing and debugging modelling code will help you understand how complex workloads behave and how to test whether a model captures that behaviour. Reviews and feedback will help you develop your engineering judgement and explain the trade‑offs you find.

Working with architects, engineers and machine learning researchers will show you how modelling results inform hardware decisions and how your work connects to the wider computing system.

What we're looking f or

• Bachelor’s/ Master’s degree, or equivalent experience, in Computer Science, Maths, Machine Learning, Data Science or a related field
• Strong C++ programming skills, gained through study, projects, personal coding or practical experience
• An understanding of computer science fundamentals and an interest in lower‑level software
• The ability to debug complex problems and explain your thinking clearly, with exposure to debugging tools, performance analysis, testing, version control or collaborative software development practices
• C uriosity about processor architecture, hardware simulation, performance modelling or systems behaviour, and a willingness to ask questions and learn through feedback

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.

• 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.