Description
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 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.
You will work closely with researchers to generate ideas and translate them into scalable implementations, contributing to publications and projects that help to steer the future of AI hardware.
Responsibilities and Duties
- Generate AI/ML ideas, design experiments, implement them & evaluate results.
- Prepare, submit & present your work to AI conferences and workshops.
- Provide technical insight to internal teams by designing experiments and delivering clear, actionable reports.
- Collaborate with researchers, silicon and software engineers at Graphcore to help define, build and test Graphcore’s next generation of AI hardware.
About you:
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
Desirable:
- Mathematics skills to support the above: calculus, probability theory and linear algebra.
- Experience submitting papers to international scientific conferences or workshops.
Benefits
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.