Senior Kubernetes Software Engineer (Go)

Salary Range: PLN 303,800 - 411,000

Subject to alignment to the responsibilities and duties of the role

About Graphcore

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.

Graphcore is building the software that powers a new era of high-performance AI compute. As a Senior Kubernetes Software Engineer, you’ll develop Go services that integrate our accelerator hardware into Kubernetes clusters—making AI compute effortless, scalable, and K8s native.

This is a hands-on engineering role where you will own SW components and  work at the intersection of software, hardware and cloud platforms.

• →

  Develop production-grade Go services that expose our accelerator capabilities to end users.

• →

  Build CRDs, operators and other Kubernetes components to provide a seamless experience for ML and platform teams.

• →

  Ensure reliability, performance, and scalability of Kubernetes-based AI-compute infrastructure.

• →

  Partner with cross-functional teams (hardware, cloud, ML) on architecture, design, and feature roadmaps.

• →

  Drive improvements in code quality, observability, automation and developer experience.

• Strong Go programming experience.

• Bachelor’s degree in Computer Science, Engineering, or related field, or equivalent experience, with at least 10 years of software development experience. 

• Deep knowledge of Kubernetes architecture. 

• Solid Linux understanding and cloud-native mindset.

• Ability to lead technical initiatives and mentor other engineers.

• English- C1 level.

• Familiarity with machine learning-related technologies within the Kubernetes ecosystem e.g. Kubeflow, Karmada, Kueue, KubeVirt, Kata containers, Volcano is highly desirable.

• Knowledge of RDMA networks is considered an asset. 

• Familiarity with other workload managers, such as Ray and SLURM, is considered an asset.