About Graphcore

How often do you get the chance to build a technology that transforms the future of humanity? Graphcore products have set the standard in made-for-AI compute hardware and software, gaining global attention and industry acclaim. Now we are developing the next generation of artificial intelligence compute with systems that will allow AI researchers to develop more advanced models, help scientists unlock exciting new discoveries, and power companies around the world as they put AI at the heart of their business. Graphcore recently joined SoftBank Group – bringing large and ongoing investment from one of the world’s leading backers of innovative AI companies.

Job Summary

As a Cloud Software Engineer, you will play a key role in enabling new AI accelerator hardware within Kubernetes environments. You will be responsible for developing device plugins in Go, ensuring seamless integration with existing Kubernetes clusters, and providing a native Kubernetes end user experience. This role requires a strong foundation in software development, container orchestration technologies and cloud computing.

Responsibilities and Duties

• Develop and maintain device plugins in Go for new AI accelerator hardware integration in Kubernetes.
• Ensure seamless integration of new hardware with existing Kubernetes clusters.
• Collaborate with cross-functional teams to design, implement, and test new features.
• Participate in code reviews, design discussions, and troubleshooting sessions.
• Maintain high standards of software quality within the team by following good practices and habits.
• Write and maintain comprehensive documentation for your code and the overall project.
• Stay up-to-date with the latest trends and technologies in cloud computing and Kubernetes.

Skills and Experience

• Bachelor’s degree in Computer Science, Engineering, or a related field.
• At least 3 years of experience in software development, preferably in cloud environments.
• Strong working knowledge of Python or Go programming language.
• Experience with Kubernetes is essential, with a preference for candidates holding a Certified Kubernetes Administrator (CKA) certification.
• Familiarity with container orchestration, and cloud-native development.
• Knowledge of cloud computing platforms such as Azure, GCP, AWS and their services.
• Familiarity with machine learning-related technologies within the Kubernetes ecosystem e.g. Kubeflow, KubeVirt, Kata containers, Volcano is highly desirable.
• Knowledge of RDMA networks is considered an asset.
• Experience with CI/CD pipelines and DevOps tools e.g. GitHub/GitLab.
• Excellent communication and teamwork skills.
• English- B2 level.

Benefits