AI Research Engineer

Навыки

• C++
• CUDA / ONNX / TensorRT
• Machine Learning
• Python
• PyTorch
• Статистика

О компании и продукте

• 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 engineer 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. We are therefore looking for individuals who combine strong machine learning experience with practical engineering skills to deliver impactful AI research. We are seeking AI researchers with strong software engineering experience, particularly in lower-level programming and performance optimisation for hardware efficiency. Our research spans a broad range of topics, including efficient training and inference, world models, life sciences, reinforcement learning, and beyond.

Требования

• Essential
• Master’s, PhD or equivalent experience in a technical discipline (e.g., Maths, Statistics, Computer Science, Physics, Chemistry)
• 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
• Lower-level programming for hardware efficiency, e.g. C++/CUDA/Triton
• Practical familiarity with hardware capabilities for deep learning – threads, caches, vector & matrix engines, data dependencies, bus widths and throttling
• Practical familiarity with software stacks for deep learning – compilation, kernel fusion, XLA/ATen ops, streams, and asynchronous execution

Будет плюсом

• Mathematics skills to support the above: calculus, probability theory and linear algebra
• Experience submitting papers to international scientific conferences or workshops

Условия

• 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

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