Canonical is a leading provider of open source software and operating systems to the global enterprise and technology markets. Our platform, Ubuntu, is very widely used in breakthrough enterprise initiatives such as public cloud, data science, AI, engineering innovation and IoT. Our customers include the world's leading public cloud and silicon providers, and industry leaders in many sectors. The company is a pioneer of global distributed collaboration, with 1000+ colleagues in 70+ countries and very few roles based in offices. The company is founder led, profitable and growing.
We are hiring Python and Kubernetes Specialist Engineers focused on Data, AI/ML and Analytics Solutions to join our teams building open source solutions for public cloud and private infrastructure.
As a software engineer on the team, you'll collaborate on an end-to-end data analytics and mlops solution composed of popular, open-source, machine learning tools, such as Kubeflow, MLFlow, DVC, and Feast. You may also work on workflow, ETL, data governance and visualization tools like Apache SuperSet, dbt,



and Temporal, or data warehouse solutions such as Apache Trino, or ClickHouse. Your team will own a solution from the analytics and machine learning space, and integrate with the solutions from other teams to build the world's best end-to-end data platform. These solutions may be run on servers or on the cloud, on machines or on Kubernetes, on developer desktops, or as web services.
We serve the needs of individuals and community members as much as the needs of our General 2000 and Fortune 500 customers; Location: This initiative spans many teams that are home-based and in multiple time zones. Develop your understanding of the entire Linux stack, from kernel, networking, and storage, to the application layer
Design, build and maintain solutions that will be deployed on public and private clouds and local workstations
Work with both Kubernetes and machine-oriented open source applications
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📌 Graduate Software Engineer (Murcia)
🏢 Canonical
📍 Murcia