At Graphcore, we're building the future of AI compute. We're a team of semiconductor, software and AI experts, with deep experience in creating the complete AI compute stack - from silicon and software to infrastructure at datacenter scale. As part of the SoftBank Group, backed by significant long-term investment, we are delivering key technology into the fast-growing SoftBank AI ecosystem. To meet the vast and exciting AI opportunity, Graphcore is expanding its teams around the world. We are bringing together the brightest minds to solve the toughest problems, in a place where everyone has the opportunity to make an impact on the company, our products and the future of artificial intelligence.
As a Research Scientist at Graphcore, you will advance AI research at the intersection of visual generative modelling, multimodal learning, world models and hardware-aware machine learning. You will explore new model architectures, training methods and deployment strategies with applications in embodied AI, robotics and autonomous systems. Example research directions could include efficient video generation, diffusion and flow-based models, multimodal representation learning, world models for agents, or analysis of how emerging generative AI workloads influence future AI accelerators.
This role sits at the interface between frontier model research and AI hardware. Specialised hardware has been a key driver of AI progress over the last decade, and we believe that hardware-aware AI algorithms and AI-aware hardware developments will continue to be critical to advancing this field. We are looking for researchers and engineers with the theoretical depth, practical judgement and implementation skills to turn ambitious ideas into rigorous experiments, publications and technical insights that influence the future of AI compute.
Graphcore Research participates in both fundamental and applied research to characterise the computational requirements of machine intelligence and to demonstrate how hardware can drive the next generation of innovative AI models. We publish at leading AI/ML conferences, including NeurIPS, ICML and ICLR, as well as specialist workshops, and collaborate with other research teams and organisations across the world.
We pride ourselves on being a supportive and collaborative team, where we organise around individual research interests and solve problems together. Our work spans efficient compute, model scaling, distributed training and inference, and AI models for multiple modalities and applications, including sequence- and graph-based data. We're based across London, Cambridge and Bristol, with projects and discussions that involve all our locations.
Perhaps the best way to get an idea of what we're all about is to read one of our papers or an article on our blog. If you're excited to work at the cutting edge of AI and want to help shape the hardware and software systems that drive the future of AI compute, we'd love to hear from you!
- Develop and evaluate new ideas in visual generative AI, multimodal modelling and world models, from initial hypothesis through experiment design, implementation, analysis and publication.
- Prepare, submit and present your work to AI conferences and workshops.
- Work with researchers, software engineers and silicon teams to understand how emerging AI workloads can shape, and be shaped by, future Graphcore hardware and software systems.
Essential:
- Master's, PhD or equivalent experience in a technical discipline (e.g., Mathematics, Statistics, Computer Science, Physics, Chemistry, Biomedical Engineering).
- Experience in visual generative AI, visual understanding or world models.
- Strong Python programming skills using a modern deep learning framework, e.g. PyTorch or JAX.
- Familiarity with deep learning fundamentals, including model architectures, optimisation, evaluation and scaling.
- Ability to design, execute, analyse and clearly communicate ML experiments.
- Mathematical foundations to support the above, including calculus, probability theory and linear algebra.
- Evidence of research ability, such as conference or workshop submissions, publications, technical reports, open-source projects or impactful industrial research.
Desirable:
- Experience with multimodal reasoning or generation, action-conditioned models, embodied AI, robotics or autonomous systems.
- Lower-level programming for hardware efficiency, e.g. C++/CUDA/Triton.
- Practical familiarity with hardware considerations for deep learning, such as parallelism, memory hierarchy, vector and matrix engines, data movement, bandwidth limits and performance bottlenecks.
- Practical familiarity with deep learning software stacks, such as graph compilation, kernel fusion, XLA/ATen operations, streams and asynchronous execution.
In addition to a competitive salary, Graphcore offers flexible working, a generous annual leave policy, private medical insurance and health cash plan, a dental plan, pension (matched up to 5%), life assurance and income protection. We have a generous parental leave policy and an employee assistance programme (which includes health, mental wellbeing, and bereavement support). We offer a range of healthy food and snacks at our central Bristol office and have our own barista bar! We welcome people of different backgrounds and experiences; we're committed to building an inclusive work environment that makes Graphcore a great home for everyone. We offer an equal opportunity process and understand that there are visible and invisible differences in all of us. We can provide a flexible approach to interview and encourage you to chat to us if you require any reasonable adjustments.
Applicants for this position must hold the right to work in the UK. Unfortunately at this time, we are unable to provide visa sponsorship or support for visa applications
