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 to the global enterprise and technology markets. Our platform, Ubuntu, is widely used in breakthrough enterprise initiatives such as public cloud, data science, AI, engineering innovation and IoT.

The company is founder‑led, profitable and growing. We are hiring Python and Kubernetes Specialist Engineers focused on Data, Workflows, 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 end‑to‑end data analytics and MLOps solutions composed of popular, open‑source, machine‑learning tools such as Kubeflow, MLFlow, DVC, and Feast. You may also work on ETL, data governance and visualization tools like Apache Superset, dbt, workflow orchestration tools such as Airflow and Temporal, or data warehouse solutions such as Apache Trino or Click House.

These solutions may 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 our Global 2000 and Fortune 500 customers; we provide our core work for free and offer Pro subscriptions for personal use at no cost. Our goal is to enable more people to enjoy the benefits of open source, regardless of their circumstances.

Location: This initiative spans many teams that are home‑based and operate in multiple time zones. We believe in distributed collaboration but also ensure that colleagues have company during their work hours! Successful candidates will join a team where most members and their manager are broadly in the same time zone so that they can collaborate consistently.

• Develop 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, and 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 with upstream and Ubuntu communities.
• Generate and discuss ideas, and collaborate on finding good solutions.

• Professional or academic software delivery using Python.
• Exceptional academic track record from high school through university.
• Undergraduate degree in a technical subject or a compelling narrative about an alternative chosen 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.
• The 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 organization.
• 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…