Python and Kubernetes Software Engineer

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. #J-18808-Ljbffr