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Senior Cloud Engineer (K8S)

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Posted

24 days

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About 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.

Job Summary
We are looking for a Senior Engineer to join our Cloud Platform Team and help develop and deploy clouds and services. Working closely with our colleagues in Software Platform, Datacentre Operations and Product Development teams, you will deploy services on our fleet of cutting-edge AI systems. As part of our Software Platform organisation, you will be involved in the cloud integration, validation, performance benchmarking, optimisation, and development of our high-performance AI solutions. These include in-house AI systems alongside off-the-shelf high-performance servers, switches and storage solutions. This is a hand-on technical role requiring a solid background in the use of cloud infrastructure, deployment using Infrastructure-as-Code, observability, high-performance networking and storage systems. You may have been working in an IT organisation, a datacentre, a cloud provider or as a developer of orchestration or cloud services.

The Software Platform team at Graphcore

We build Graphcore products into large-scale AI solutions for our customers and the Cloud Platform Team is responsible for providing such systems to both internal users via private clouds and customers via our own public clouds. Often the internal systems will be using and developing pre-release hardware and software, so it’s vital you are comfortable with unproven components.

Responsibilities and Duties

  • Develop and operate Kubernetes-managed end-user services on our private clouds and support internal users in their use. You will turn end-user and product requirements into deployed services.
  • Work with our Datacentre Operations Engineers to maintain and operate the fleet of AI systems at peak performance in our private clouds.
  • Configure and test new Graphcore AI hardware and systems using Continuous Deployment and Infrastructure-as-code in internal and external datacentres.

Skills and Experience (all required)

  • Bachelor's degree or equivalent practical experience in a relevant subject.
  • Experience with managing production Kubernetes clusters and workloads with a continuous delivery tool such as ArgoCD.
  • Solid software engineering or IT experience with a proven track record of delivering technical output as an individual contributor.
  • Experience working in an AGILE and SCRUM framework, including understanding of priorities, risks, issues, impacts and constraints.
  • Strong proven Linux scripting ability (bash, python, awk, sed).
  • Strong proven Linux system administration (Ubuntu, RHEL and variants).
  • Experience with a version control system (preferably Git) and using it to manage system configuration or automation.
  • Experience with Continuous Integration or testing pipelines using GitLab, GitHub or similar.
  • A solid hands-on understanding of the technologies underpinning cloud services (APIs, virtualisation of CPUs, IO, systems), virtual networks, block storage, resource management and monitoring.
  • Experience with IAC automation tools (Terraform/OpenTofu
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Aplyr's read

Graphcore is a cutting-edge semiconductor company focusing on AI and machine learning hardware, appealing to engineers interested in high-performance computing and innovative chip design.

Synthesized from recent postings & public sources

What's promising

  • Graphcore's IPU technology is at the forefront of AI hardware innovation.
  • The company has secured significant funding, indicating strong investor confidence.
  • Graphcore's partnerships with major tech firms enhance its industry credibility.

What to watch

  • Graphcore faces intense competition from established players like NVIDIA.
  • The company's financials are not publicly available, limiting transparency.
  • Market adoption of IPU technology remains uncertain in the face of GPU dominance.

Why Graphcore

  • Graphcore's IPU is specifically designed for AI workloads, unlike traditional CPUs and GPUs.
  • The company emphasizes a software ecosystem tailored to its hardware.
  • Graphcore is known for its collaborative culture and focus on cutting-edge research.

Aplyr’s read is generated by AI from public sources. Was it useful?

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