Python and Kubernetes Software Engineer - Data, Workflows, AI​/ML & Analytics

Python and Kubernetes Software Engineer - Data, Workflows, AI/ML & Analytics

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Canonical is a leading provider of open source software and operating systems. Our platform, Ubuntu, is widely used in enterprises for public cloud, data science, AI, engineering innovation and IoT. The company is founder‑led, profitable and growing, and we are hiring specialists focused on Data, Workflows, AI/ML and Analytics Solutions.

• 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.
• Master distributed systems concepts such as observability, identity, tracing.
• Work with both Kubernetes and machine‑oriented open source applications.
• Collaborate proactively with a distributed team of engineers, designers and product managers.
• Debug issues and interact in public with upstream and Ubuntu communities.
• Generate and discuss ideas, and collaborate on finding good solutions.

• Professional delivery using Python.
• Exceptional academic track record from high school and university.
• Undergraduate degree in a technical subject or a compelling narrative about an alternative path.
• Confidence to respectfully speak up, exchange feedback, and share ideas without hesitation.
• Track record of going above‑and‑beyond expectations to achieve outstanding results.
• Passion for technology evidenced by personal projects and initiatives.
• Work ethic and confidence to shine alongside motivated colleagues.
• Professional written and spoken English with excellent presentation skills.
• Experience with Linux (Debian or Ubuntu preferred).
• Excellent interpersonal skills, curiosity, flexibility, and accountability.
• Appreciative of diversity, polite and effective in a multi‑cultural, multi‑national organisation.
• Thoughtfulness and self‑motivation.
• Result‑oriented, with a personal drive to meet commitments.
• Ability to travel twice a year for company events up to two weeks long.

• Proven track record of building highly automated machine learning solutions, data pipelines, or orchestrating workflows for the cloud.
• Hands‑on experience with machine learning libraries or tools.
• Experience with container technologies (Docker, LXD, Kubernetes, etc.).
• Experience with public clouds (AWS, Azure, Google Cloud).
• Working knowledge of cloud computing.
• Passionate about software quality and testing.
• Experience working on an open source project.

• Distributed work environment with twice‑yearly team sprints in person.
• Personal learning and development budget of USD 2,000 per year.
• Annual compensation review.
• Recognition rewards.
• Annual holiday leave.
• Maternity and paternity leave.
• Employee Assistance Programme.
• Opportunity to travel to new locations to meet colleagues.
• Priority Pass, and travel upgrades for long‑haul company events.

Worldwide remote with optional in‑office meetings in multiple time zones. Candidates should have a suitable time zone to collaborate effectively with the team.