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

Overview Python and Kubernetes Software Engineer - Data, Workflows, AI/ML & Analytics at Canonical. This initiative spans many teams that are home-based and in multiple time zones. We believe in distributed collaboration but we also try to ensure that colleagues have company during their work hours. Successful candidates will join a team where most members and your manager are broadly in the same time zone so that you have the benefits of constant collaboration and discussion. 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 ClickHouse. These solutions may be run on servers or on the cloud, on machines or on Kubernetes, on developer desktops, or as web services. Location note: This is a distributed role with teams across time zones. Our primary goal is to enable access to open source benefits to as many people as possible, including individuals using Pro subscriptions at no cost. Responsibilities Develop understanding of the Linux stack, from kernel, networking, and storage, to the application layer Design, build and maintain solutions deployed on public/private clouds and local workstations Master distributed systems concepts such as observability, identity, 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 finding effective solutions What we are looking for 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 share feedback and ideas respectfully Track record of going above and beyond to achieve results Passion for technology evidenced by personal projects and initiatives Work ethic and ability to work with motivated colleagues Professional written and spoken English with strong presentation skills Experience with Linux (Debian or Ubuntu preferred) Interpersonal skills, curiosity, flexibility, and accountability Appreciation of diversity and ability to work in a multi-cultural, multi-national organization Thoughtfulness and self-motivation Result-oriented with a drive to meet commitments Willingness to travel up to twice a year for company events (up to two weeks) Nice to have Proven track record of building automated ML solutions, data pipelines, or orchestrating workflows for the cloud Experience with ML libraries/tools Experience with container technologies (Docker, LXD, Kubernetes) Experience with public clouds (AWS, Azure, Google Cloud) Working knowledge of cloud computing Strong software quality and testing mindset Experience contributing to open source projects What we offer Distributed work environment with twice-yearly in-person team sprints 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 Travel upgrades for long-haul company events About Canonical Canonical is an equal opportunity employer. We are proud to foster a workplace free from discrimination. Diversity of experience, perspectives, and background create a better work environment and better products. Whatever your identity, we will give your application fair consideration. J-18808-Ljbffr

Location: Torino, Piemonte, IT

Posted Date: 9/17/2025