Research Scientist, Graphcore

• As such, we’re looking for candidates who are keen scientists and engineers, with the theoretical and practical skills needed for impactful AI research
• We are looking for researchers with experience of AI in low-power, edge and embodied scenarios such as robotics, autonomous driving and augmented/virtual reality
• We are interested in the training and deployment of multimodal AI models in these contexts, covering areas such as world models, real-time computer vision, generating and reasoning over audio/video streams
• Master’s, PhD or equivalent experience in a technical discipline (e.g., Maths, Statistics, Computer Science, Physics, Chemistry, Biomedical Engineering)
• Experience in embodied AI, world models or robotics
• Python programming in a modern deep learning framework, e.g. PyTorch or JAX
• Familiar with deep learning fundamentals: models, optimisation, evaluation and scaling
• Capable of designing, executing and reporting from ML experiments
• Mathematics skills to support the above: calculus, probability theory and linear algebra
• Experience submitting papers to international scientific conferences or workshops

Desirable

• As a researcher at Graphcore, you will contribute to the advancement of AI research, investigating new ideas that push the limits on important AI/ML problems
• Specialised hardware has been the key driver of the progress of AI 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 exciting field
• 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 (NeurIPS, ICML, 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 our individual research interests to solve problems together in domains such as efficient compute, model scaling and distributed training and inference of AI models for multiple modalities and applications, including for sequence- and graph-based data
• Generate AI/ML ideas, design experiments, implement them & evaluate results
• Prepare, submit & present your work to AI conferences and workshops
• Collaborate with researchers, silicon and software engineers at Graphcore to help define, build and test Graphcore’s next generation of AI hardware