--- title: 'Senior Machine Learning Engineer (Large Systems) at Graphcore' canonical: 'https://feeny.ai/job/senior-machine-learning-engineer-large-systems-graphcore-cambridge-3e8ndgscz15d' type: 'job' last_seen: '2026-10-13' --- # Senior Machine Learning Engineer (Large Systems) at Graphcore - **Company:** Graphcore - **Location:** Cambridge, MA - **Posted:** 2026-10-09 - **Last confirmed live:** 2026-10-13 - **Apply:** https://job-boards.greenhouse.io/graphcore/jobs/8881595002 ## Job description Location: Bristol, London or Cambridge, UK ## About the job Help scale state-of-the art AI models across thousands of accelerators. As a Senior Machine Learning Engineer in the Applied AI team, you will contribute to advancing AI technology by developing and optimising new and existing AI models for our specialised hardware. You will work on large scale systems where performance is critical to the success of our projects. Having visibility of the entire pipeline from novel accelerator hardware to state-of-the-art AI applications, and the software stack in-between, you will play a critical role in identifying opportunities to innovate and differentiate Graphcore’s technology. Furthermore, you’ll work closely with researchers in a rapidly-evolving field, where even the most senior engineers are constantly learning and adapting to exciting new challenges. We seek engineers with strong technical foundations who are curious and eager to understand and advance AI model implementation, at scale. We currently have multiple opportunities available in the team at Senior, Staff and Principal level and offer flexibility through a hybrid working model, from any of our UK offices. If you're excited about advancing the next generation of AI models on cutting-edge hardware, we’d love to hear from you! The team and culture The Applied AI team’s role is to be proxies for our customers, we need to understand the latest AI models, applications, and software, as well as our own hardware and software stack, to ensure that Graphcore’s technology works seamlessly with the AI ecosystem and at scale. Our work spans from low-level kernel development and optimisation for novel hardware through to implementing and scaling research-level algorithms for the latest AI models. We collaborate with the Research team to develop and publish novel ideas in domains such as efficient compute, model scaling and distributed training and inference of AI models for multiple modalities and applications. ## Responsibilities - Implement and train state-of-the-art machine learning models and optimise for performance, accuracy and scalability across systems comprising 1000s of accelerators. - Benchmark and profile ML models to identify performance bottlenecks. - Develop deep understanding across the software stack in order to optimise kernel implementations. - Test and evaluate new internal software releases, provide feedback to software engineering teams, make necessary code fixes, and conduct code reviews. - Design and conduct experiments on novel AI methods and evaluate results. - Collaborate with Research, Software, and Product teams to define, build, and test Graphcore’s next generation of AI hardware. - Engage with AI community and keep in touch with the latest developments in AI. ## What we’re looking for Essential: - Bachelor/Master's/PhD or equivalent experience in Machine Learning, Computer Science, Maths, Data Science, or related field. - Proficiency in deep learning frameworks like PyTorch/JAX. - Strong Python or C++ software development skills. - Expertise in hardware-accelerated deep learning from model training to optimisation and evaluation. - Capable of designing, executing and reporting from ML experiments. - Well-developed understanding of performance bottlenecks and how to overcome them. - Ability to move quickly in a fast-moving field. - Enjoy cross-functional work collaborating with other teams. - Strong communicator - able to explain complex technical concepts to different audiences. Desirable: - Experience in one or more of: - MLOps for Kubernetes-based clusters - Building production systems with large language models - Efficient computing based on low-precision arithmetic. - Experience writing C++/Triton/CUDA kernels for performance optimisation of ML models. - Experience in distributed training or inference of ML models across 64+ accelerators. - Familiarity with HPC systems and networking including Infiniband, NVLink, RoCE technologies, and cloud computing platforms. - Have contributed to open-source projects or published research papers in relevant fields. - Keen to present, publish and deliver talks in the AI community. ## Benefits - Flexible working: Balance your work and personal life with greater flexibility - Generous leave: Take time to rest, recharge and enjoy life outside of work - 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 drinks 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. Join the Team at Graphcore Graphcore is one of the world’s leading innovators in Artificial Intelligence compute. It is developing hardware, software and systems infrastructure that will unlock the next generation of AI breakthroughs and power the widespread adoption of AI solutions across every industry. As part of the SoftBank Group, Graphcore is a member of an elite family of companies responsible for some of the world’s most transformative technologies. Together, they share a bold vision: to enable Artificial Intelligence and ensure its benefits are accessible to everyone. Graphcore’s teams are drawn from diverse backgrounds and bring a broad range of skills and perspectives. A melting pot of AI research specialists, silicon designers, software engineers and systems architects, Graphcore brings together deep expertise to solve complex problems and deliver meaningful progress in AI compute. Sponsorship Applicants must have the legal right to work in the UK. Unfortunately, we are unable to provide visa sponsorship for this role. ## 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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