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

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 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 founder-led, profitable and growing, with 1000+ colleagues in 70+ countries.

Most roles are remote, with very few offices. Teams meet two to four times per year in person, in interesting locations around the world, to align on strategy and execution.

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 be run on servers or on 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 believe in distributed collaboration, but we also strive to ensure 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 to enable constant collaboration and discussion.

• 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 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

• 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…