Quality Assurance Engineer Workload Management

Graphcore

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profile Job Location:

Gdańsk - Poland

profile Monthly Salary: Not Disclosed
Posted on: 8 hours ago
Vacancies: 1 Vacancy

Job Summary

Salary Range: PLN 260400 - 352200

Subject to alignment to the responsibilities and duties of the role.

About Graphcore

At Graphcore were building the future of AI 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 part of the SoftBank Group backed by significant long-term investment we are delivering key technology into the fast-growing SoftBank AI meet the vast and exciting AI opportunity Graphcore is expanding its teams around the 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.

The Role

We are seeking aQuality Assurance Engineerto join ourWorkload Management team whichis responsible forenabling next-generation AI accelerator hardware within Kubernetes clusters.

In this role you will contribute to the validation of Kubernetes integrations that allow new acceleratorto be scheduled orchestrated and utilised efficiently across distributed environments.

Working closely with software engineers and infrastructure teams you will help ensure that our workload management stack-including scheduling resource allocation and device management-operatesreliably in production environments. The role combines automation engineering with a systems-level understanding of distributed platforms helping ensure our solutions are robust scalable and ready for real-world deployment.

Responsibilities

  • Design develop andmaintainautomated test suitesfor Kubernetes integration components.
  • Develop end-to-end integration and system tests tovalidatescheduling and resource allocation across Kubernetes clusters.
  • Identify document and track defects while working closely with engineering teams to investigate root causes and verifyfixes.
  • Contribute to design ofCI/CD pipelines.
  • Validate the scalability performance and reliability of workload orchestration.
  • Improvetest coverage test stability and observabilityacross distributed system components.
  • Collaborate with development teams to definequality standards test strategies and validation plansearly in the development lifecycle.

Skills and Experience

Essential

  • Programming experience inPython.
  • Hands-on experience withRobot Frameworkor similar automation frameworks.
  • Goodunderstanding of Linux systems.
  • Experience withCI/CD systemssuch as GitLab CIorGitHub Actions.
  • Experience testingdistributed systems.
  • Ability to debug complex issues across multiple system layers (Kubernetes infrastructure applications).
  • Goodanalytical and problem-solving skills.

Desirable

  • ExperiencevalidatingKubernetes integrations.
  • Understanding ofAItrainingandinference workloads and their orchestration requirements.
  • Experience testing cloud-native systems and containerised environments.

Benefits

In addition to a competitive salary annual leave policy medical and dental health plans a gym card and employee pension (matched up to 4%). We review our benefits on a yearly basis to ensure we offer a valuable and rewarding benefits programme to our employees. We welcome people of different backgrounds and experiences; were committed to building an inclusive work environment that makes Graphcore a great home for everyone. We offer an equal opportunity process and understand that there are visible and invisible differences in all of us. We can provide a flexible approach to interview and encourage you to chat to us if you require any reasonable adjustments.


Required Experience:

IC

Salary Range: PLN 260400 - 352200Subject to alignment to the responsibilities and duties of the role.About GraphcoreAt Graphcore were building the future of AI a team of semiconductor software and AI experts with deep experience in creating the complete AI compute stack - from silicon and software ...
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