Graphcore Logo

Graphcore

Graduate Software Engineer, Accelerator Modelling 2027

Posted 3 Days Ago
Be an Early Applicant
Hybrid
Bristol, England
Entry level
Hybrid
Bristol, England
Entry level
Develop, test, and refine C++ models and simulations for future AI accelerators. Analyze workload behavior, performance, power consumption, and scalability to inform hardware architecture decisions. Debug complex modelling code, support distributed modelling environments, and collaborate with architecture, hardware, software, and machine learning teams. The two-year graduate programme provides hands-on experience in software development, hardware simulation, performance modelling, and engineering judgment.
The summary above was generated by AI

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.

What you’ll work on 

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 for 
  • 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. 

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 and what to expect 

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.

Ready to put your learning into practice? Start your career in a permanent Software Engineer role in Accelerator Modelling, with two years of hands-on learning through the Graphcore Graduate Programme. Apply now and help shape what comes next. 

Graphcore London, England Office

Graphcore London Office Office

Lynton House, 7-12 Tavistock Square, London, United Kingdom, WC1H 9LT

Similar Jobs at Graphcore

2 Days Ago
Hybrid
Entry level
Entry level
Artificial Intelligence • Semiconductor
Architect high-performance SoC subsystems for AI accelerator silicon, translating product requirements into specifications and evaluating implementation trade-offs. Responsibilities include subsystem modeling, validation, third-party IP assessment, vendor collaboration, integration, silicon bring-up, characterization, and evaluation. The role partners with processor, hardware, verification, software, and systems teams, resolves complex bugs, improves engineering processes, and mentors engineers.
Top Skills: Ai AcceleratorsHardware VerificationRtlSilicon DesignSoc Architecture
2 Days Ago
Hybrid
Entry level
Entry level
Artificial Intelligence • Semiconductor
Develops and deploys hardware tests for circuit boards and PCB assemblies, from design analysis through factory and field support. Analyzes PCB testability and manufacturing defect risks, builds boundary scan and embedded functional tests, and improves defect coverage and diagnostics. Works with hardware design teams, manufacturing operations, and contract manufacturers to identify component-level electronic failures and strengthen inspection and test methods.
Top Skills: Automated Optical Inspection (Aoi)Automated X-Ray Inspection (Axi)Boundary ScanDigital ElectronicsEmbedded Functional TestingPcb ManufacturingPcbaSurface-Mount Technology (Smt)
2 Days Ago
Hybrid
Entry level
Entry level
Artificial Intelligence • Semiconductor
Design, implement, optimize, and support PyTorch, Triton, and related framework features for Graphcore accelerators. Contribute to upstream PyTorch, maintain Python and C++ extensions, integrate compiler backend capabilities with torch.compile, review code, write documentation, and support users. Collaborate with software, AI/ML, research, and hardware teams while working in large open-source codebases.
Top Skills: C++GitGraphcore AcceleratorsPythonPyTorchTorch.CompileTriton

What you need to know about the London Tech Scene

London isn't just a hub for established businesses; it's also a nursery for innovation. Boasting one of the most recognized fintech ecosystems in Europe, attracting billions in investments each year, London's success has made it a go-to destination for startups looking to make their mark. Top U.K. companies like Hoptin, Moneybox and Marshmallow have already made the city their base — yet fintech is just the beginning. From healthtech to renewable energy to cybersecurity and beyond, the city's startups are breaking new ground across a range of industries.

Sign up now Access later

Create Free Account

Please log in or sign up to report this job.

Create Free Account