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Graphcore

Delivers IPU-powered AI cloud services

Staff Cloud Software Engineer

Backend EngineeringConfirmed live in the last 24 hours
Full-timeGdańsk, Poland

About the Job

Requirements

  • Strong Go engineering experience, including significant experience delivering complex production software.
  • Deep knowledge of Kubernetes architecture, including custom resource definitions (CRDs), operators, and cloud-native integration patterns.
  • Solid understanding of Linux and the ability to debug issues across distributed systems.
  • Experience leading technical initiatives and mentoring engineers through design, review, and delivery.
  • Ability to improve code quality, observability, automation, and developer experience.
  • C1-level English communication skills and confidence working across hardware, cloud, and machine learning teams.
  • Must have the legal right to work in Poland.

Responsibilities

  • Build Go services that connect accelerator hardware with Kubernetes.
  • Own software components that make complex compute capability usable as a platform experience.
  • Design production services for AI workloads to discover, access, and scale across cluster infrastructure, incorporating reliability, performance, and observability into the architecture.
  • Build custom resource definitions, operators, and Kubernetes components for machine learning and platform teams.
  • Partner with hardware, cloud, and machine learning engineers on design choices and roadmap priorities.
  • Own technical areas, challenge assumptions, and move important work forward.
  • Mentor engineers, raise code quality, and help define how Graphcore delivers cloud-native AI compute.

About the Company

Graphcore

Delivers IPU-powered AI cloud services

Graphcore.ai focuses on building and delivering Intelligence Processing Units (IPUs) and related AI services for enterprises. It provides IPU-powered cloud services, pre-trained AI models, optimized inference engines, and APIs on a subscription basis with on-demand pricing and free tiers through cloud partners. The IPUs accelerate AI workloads and enable scalable, cost-efficient AI deployment in enterprise applications. The company differentiates itself through specialized IPU hardware and optimized software stack, plus partnerships with cloud providers to reach customers, rather than relying on generic hardware. The goal is to help businesses scale AI-powered products and operations efficiently by offering flexible, scalable compute and ready-to-use AI components.

Company size
501-1,000
Company stage
Growth Equity (Non-Venture Capital)
Total funding
$1.1B
Headquarters
Bristol, United Kingdom
Founded
2016

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