About the job
About Graphcore
At Graphcore, we are pioneering the future of AI computation. Our team consists of semiconductor, software, and AI specialists with extensive experience in creating a complete AI compute stack, from silicon and software to infrastructure at datacenter scale. As a proud member of the SoftBank Group, we are supported by significant long-term investments, allowing us to deliver vital technology to the rapidly expanding SoftBank AI ecosystem. To seize the immense and exciting opportunities in AI, Graphcore is actively expanding its teams globally, uniting the brightest minds to tackle the most challenging problems in an environment where everyone can significantly impact the company, its products, and the future of artificial intelligence.
Job Summary
In the role of Senior Machine Learning Engineer within the Applied AI team at Graphcore, you will play a crucial part in advancing AI technology by developing and optimizing AI models specifically designed for our specialized hardware. You will engage with large-scale systems where performance is paramount to the success of our initiatives. Collaborating closely with both the Software Development and Research teams, you will be instrumental in identifying innovative opportunities that set Graphcore’s technology apart. We are looking for engineers with robust technical skills and a deep understanding of large-scale AI model implementation, eager to make a meaningful impact in this fast-evolving field.
The Team
The Applied AI team's mission is to serve as advocates for our customers. We continually strive to understand the latest AI models, applications, and software to ensure that Graphcore’s technology integrates seamlessly with the AI ecosystem and operates efficiently at scale. Our responsibilities include building reference applications, optimizing key software libraries (including kernel efficiency on our hardware), and collaborating with the Research team to develop and publish innovative ideas across domains such as efficient computation, model scaling, and distributed training and inference of AI models across various modalities and applications. If you are passionate about advancing the next generation of AI models on cutting-edge hardware, we would love to hear from you!
