Overview Canonical is a leading provider of open source software and operating systems to the global enterprise and technology markets. Our platform, Ubuntu, is widely used in enterprise initiatives such as public cloud, data science, AI, engineering innovation and IoT. The company is founder led, profitable and growing, with 1000+ colleagues in 70+ countries and most roles based remotely. We hire 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. You may also work on workflow, ETL, data governance and visualization tools, or data warehouse solutions. Your team will own a solution from the analytics and machine learning space and integrate with other teams to build a comprehensive data platform. These solutions may run on servers or in the cloud, on machines or on Kubernetes, on developer desktops, or as web services.
Location: This initiative spans many teams that are home-based and in multiple time zones. We value distributed collaboration and aim for colleagues to be in the same time zone for constant collaboration and discussion where possible.
Responsibilities Develop understanding of the Linux stack, from kernel and networking to the application layer
Design, build and maintain solutions deployed on public and private clouds and local workstations
Master distributed systems concepts such as observability, identity, and tracing
Work with Kubernetes and machine-oriented open source applications
Collaborate with a distributed team of engineers, designers and product managers
Debug issues and interact with upstream and Ubuntu communities
Generate ideas and collaborate on effective solutions
What we are looking for in you Professional or academic software delivery using Python
Strong academic record from high school and university
Undergraduate degree in a technical subject or a compelling alternative narrative
Confidence to respectfully speak up, exchange feedback, and share ideas
Track record of going above and beyond to achieve results
Passion for technology demonstrated by personal projects
Strong work ethic and ability to collaborate with motivated colleagues
Professional written and spoken English with excellent presentation skills
Experience with Linux (Debian or Ubuntu preferred)
Interpersonal skills, curiosity, flexibility, accountability
Appreciation for diversity and ability to work in a multi-cultural, multi-national organization
Thoughtfulness and self-motivation
Result-oriented with commitment to meet objectives
Ability to travel twice a year for company events up to two weeks
Nice to have Hands-on experience with machine learning libraries or tools
Experience building automated machine learning solutions for the cloud
Experience with container technologies (Docker, LXD, Kubernetes, etc.)
Experience with public clouds (AWS, Azure, Google Cloud)
Working knowledge of cloud computing
Passion for software quality and testing
Experience contributing to an open source project
What we offer Distributed work environment with periodic in-person team sprints
Personal learning and development budget
Annual compensation review
Recognition rewards
Annual holiday leave
Maternity and paternity leave
Employee Assistance Programme
Travel opportunities to meet colleagues
Travel upgrades for long-haul company events
About Canonical Canonical is a pioneering tech firm at the forefront of the global move to open source. We publish Ubuntu, a key open source project and platform for AI, IoT and the cloud. We recruit on a global basis and maintain high standards for those joining. Most colleagues work from home, and the role offers opportunities to think differently, work smarter, learn new skills, and raise performance.
Canonical is an equal opportunity employer
We are committed to a workplace free from discrimination. Diversity of experience and background contribute to a better environment and better products. All applicants will receive fair consideration.
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