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

About the Position

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. 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.

Responsibilities

• 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

Requirements

• 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 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

Nice to Have

• 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

We Offer

• 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 colleagues
• Priority Pass, and travel upgrades for long haul company events

About the Company

Canonical is a pioneering tech firm at the forefront of the global move to open source. As the company that publishes Ubuntu, one of the most important open source projects and the platform for AI, IoT, and the cloud, we are changing the world of software. We recruit on a global basis and set a very high standard for people joining the company. We expect excellence - in order to succeed, we need to be the best at what we do. Most colleagues at Canonical have worked from home since its inception in 2004. Working here is a step into the future, and will challenge you to think differently, work smarter, learn new skills, and raise your game.

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.