About the job
Senior: PLN 260,400 - 352,200
Staff: PLN 350,700 - 474,400
We have multiple openings available at both Senior and Staff levels based on role responsibilities and duties.
About Graphcore
At Graphcore, we are pioneering the future of AI computing.
Our dedicated team of semiconductor, software, and AI professionals possesses extensive experience in developing the full AI compute stack, from silicon and software to large-scale infrastructure.
As a proud member of the SoftBank Group, we are supported by substantial long-term investments, enabling us to deliver critical technology within the rapidly expanding SoftBank AI ecosystem.
To tackle the vast and exciting opportunities in AI, Graphcore is expanding its teams across the globe.
We unite the brightest minds to address the most challenging problems, ensuring that everyone has the chance to influence our company, products, and the future of artificial intelligence.
Job Summary
As a Senior Machine Learning Engineer in the Applied AI team at Graphcore, you will be instrumental in pushing the boundaries of AI technology by developing and optimizing AI models specifically designed for our unique hardware. Your focus will be on large systems, where performance is essential to the success of our initiatives. Collaborating closely with Software Development and Research teams, you will play a vital role in identifying innovative opportunities and differentiating Graphcore’s technology. We seek engineers with robust technical skills and a solid understanding of large-scale AI model implementation, eager to make a significant impact in this fast-evolving field.
The Team
The Applied AI team acts as a liaison for our customers, ensuring we stay abreast of the latest AI models, applications, and software to guarantee that Graphcore’s technology integrates seamlessly with the AI ecosystem and operates at scale. We develop reference applications, enhance key software libraries (e.g., optimizing kernels for efficiency on our hardware), and collaborate with the Research team to create and disseminate innovative ideas in fields such as efficient compute, model scaling, and distributed training and inference of AI models across various modalities and applications.
