--- title: 'Graduate Software Engineer, AI/ ML Test Systems 2027 at Graphcore' canonical: 'https://feeny.ai/job/graduate-software-engineer-ai-ml-test-systems-2027-graphcore-bristol-ajwhd21t6t38' type: 'job' last_seen: '2026-10-20' --- # Graduate Software Engineer, AI/ ML Test Systems 2027 at Graphcore - **Company:** Graphcore - **Location:** Bristol, United Kingdom - **Posted:** 2026-10-20 - **Last confirmed live:** 2026-10-20 - **Apply:** https://job-boards.greenhouse.io/graphcore/jobs/8894364002 ## Job description 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 software skills to work testing how AI and machine learning workloads run on Graphcore accelerator hardware. As a Graduate Software Engineer in AI/ML Test Systems, you’ll create representative machine learning workloads and analyse their numerical accuracy and performance. You’ll design tests and help improve testing strategies and infrastructure across simulated and physical hardware. You’ll also build continuous integration and continuous delivery (CI/CD) pipelines, investigate difficult problems and turn your findings into measurable improvements. Your work will connect machine learning frameworks and models with the hardware beneath them, helping improve software quality and customer experience. ## Your team and support The Software QA team combines software engineering, automation and data analysis to improve product quality and customer experience. We work extensively with industry-standard machine learning frameworks and models, including contributions to upstream open-source projects. Our team works in small squads, each with ownership of a particular area of software quality. As a graduate, you’ll have the opportunity to explore the breadth of our work, gain practical experience across different areas and discover what interests you before settling into a squad. You’ll work alongside engineers who investigate problems, share findings and collaborate closely with development teams to improve quality, security and maintainability. Test results, performance data and the needs of the wider software organisation guide our decisions. You’ll have a buddy to help you find your feet and a manager who will support your development, explore your career goals with you and help make time for learning. You’ll be encouraged to ask questions, challenge existing approaches and take initiative, with experienced colleagues to turn to for guidance as you build confidence and take ownership of your work. ## How you’ll learn and grow During the two-year programme, you’ll build practical experience across machine learning, testing, automation and performance analysis. Creating workloads and analysing results will help you understand how software behaves on accelerator hardware. Debugging issues will develop your problem-solving skills and help you connect numerical accuracy and performance to the systems running a model. Work on test infrastructure and CI/CD will show you how automated checks support software development across simulated and physical platforms. Sharing findings with development teams will help you explain technical problems clearly and turn evidence into improvements. ## What we're looking for - Bachelor’s/Master’s degree in Computer Science, Maths, Machine Learning, Data Science or a related field - Strong Python skills and proficiency in C++ - Experience working with Linux operating systems and the ability to learn new technologies quickly Exposure to machine learning frameworks such as PyTorch, JAX, Triton or TensorFlow, test automation, CI/CD, data analytics, hardware architectures or compilers would be useful. Experience with distributed workload management systems or machine learning operations (MLOps) pipelines would also be useful. These are additional strengths, rather than essential requirements. ## 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 AI/ML Test Systems, with two years of hands-on learning through the Graphcore Graduate Programme. Apply now and help shape what comes next. ## About Graphcore ## Company Overview - **One-liner**: Graphcore designs and builds the Intelligence Processing Unit (IPU), a processor purpose-built for machine intelligence, and provides a complete AI compute stack from silicon to software. - **Entity Type**: Private (wholly owned subsidiary of SoftBank Group Corp as of 2025/2026) - **Headquarters**: Bristol, England, UK - **Founded**: 2016 - **Founders**: Nigel Toon and Simon Knowles ## Core Business - **Primary industry**: AI hardware/accelerators, semiconductor design, AI software platform - **Target customers**: Cloud providers (Microsoft Azure), enterprises, AI researchers, hyperscalers - **Mission statement**: “Let innovators create the next breakthroughs in machine intelligence to enhance human potential” ## Products & Services - **[IPU (Intelligence Processing Unit)](https://www.graphcore.ai/)**: A processor designed from the ground up for machine intelligence workloads; uses a massively parallel architecture (MIMD) with fine-grained compute and on-chip memory. - **[IPU-Machine M2000](https://www.graphcore.ai/about)**: Second-generation IPU platform – a 1U server appliance housing 4 MK2 GC200 IPU processors, delivering an 8× performance uplift over the first generation. - **[C2 IPU Accelerator PCIe Card](https://www.graphcore.ai/about)**: PCIe form factor accelerator for server integration, first demonstrated at ICML 2018. - **[Poplar Software Stack](https://www.graphcore.ai/)**: Full SDK and framework integration (PyTorch, TensorFlow) that lets developers target the IPU directly. ## Market Standing - **Valuation/Market Cap**: Acquired by SoftBank Group Corp (amount undisclosed); prior to acquisition valued at $2.77 B (Series E, lead by Ontario Teachers’ Pension Plan Board). - **Key Metric**: Total funding raised prior to acquisition – over $680 M across Series A through E. - **Notable Investors/Partners**: SoftBank (owner), Microsoft (customer and investor), BMW, Samsung, Dell Technologies, Bosch, Sequoia Capital, Atomico, Fidelity, Baillie Gifford, Ontario Teachers’. - **Growth Signals**: Part of the fast-growing SoftBank AI ecosystem; expanding teams globally (Bristol, London, Cambridge, Gdańsk, Hsinchu, Bengaluru); first customer (Microsoft Azure) live since 2018. ## Competitive Advantages - **First purpose-built AI processor**: The IPU architecture is fundamentally different from GPUs – designed specifically for the sparse, parallel nature of neural network computation. - **Full stack ownership**: Graphcore controls silicon, system hardware, and software (Poplar), enabling tight optimisation across the entire compute chain. - **Cloud + on‑prem availability**: IPUs are available in the cloud on Microsoft Azure and as hardware from Dell, giving customers flexible deployment options. - **Strong IP and ecosystem**: 99+ engineering staff; deep expertise in semiconductor, systems, and AI software, backed by long-term SoftBank investment. ## Strategic Focus - **Scale AI infrastructure**: Delivering key technology into SoftBank’s global AI ecosystem and expanding the IPU platform to meet growing demand for AI compute. - **Expand into new regions**: Opening offices and hiring in India (Bengaluru) and across Europe (Gdańsk, London, Cambridge) to accelerate R&D and customer support. - **Democratise AI**: Continuing to lower the barrier for machine intelligence by providing accessible, high-efficiency hardware and software for innovators worldwide. ## Why Work Here - **Flexible hybrid work**: Employees are expected on-site three days a week, with trust and flexibility to balance work and life. - **Comprehensive benefits**: Unlimited annual leave, private medical insurance (UK), dental & health cash plan, income protection, life assurance, pension matched up to 5%, generous parental leave, and a personal development plan. - **Culture and growth**: ML reading groups, board game socials, book clubs, yoga, running, watersports, team events; strong DE+I initiatives; ambitious but supportive environment. - **Perks**: Free barista‑made coffee, snacks, and wellbeing rooms; cycle‑to‑work scheme; gym membership discount; education/training allowances. - **Purpose-driven work**: Opportunity to shape the future of AI compute and see your contributions used by global innovators. ## Sources 1. [graphcore.ai/about](https://www.graphcore.ai/about) 2. [graphcore.ai/](https://www.graphcore.ai/) 3. [graphcore.ai/careers](https://www.graphcore.ai/careers) 4. [graphcore.ai/jobs](https://www.graphcore.ai/jobs) 5. 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