Canonical is a leading provider of open source software and operating systems to the global enterprise and technology markets. Our platform, Ubuntu, is very widely used in breakthrough enterprise initiatives such as public cloud, data science, AI, engineering innovation and IoT. Our customers include the world's leading public cloud and silicon providers, and industry leaders in many sectors. The company is a pioneer of global distributed collaboration, with 1000+ colleagues in 70+ countries and very few roles based in offices. Teams meet two to four times yearly in person, in interesting locations around the world, to align on strategy and execution.

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 ClickHouse. These solutions may be 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 the needs of our Global 2000 and Fortune 500 customers; we make our primary work available free of charge and our Pro subscriptions are also available to individuals 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 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.

What your day will look like

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

What we are looking for in you

Professional or academic software delivery using Python
Exceptional academic track record from both high school and university
Undergraduate degree in a technical subject or a compelling narrative about your 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 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

Additional skills that would be nice to have

The following skills may be helpful to you in the role, but we don't expect everyone to bring all of them.

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

What we offer colleagues

We consider geographical location,

Python and Kubernetes Software Engineer - Data, Workflows, AI/ML & Analytics at Canonical Ltd.