Python and Kubernetes Software Engineer - Data, 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 breakthrough initiatives such as public cloud, data science, AI, engineering innovation, and IoT. We serve customers including the world's leading public cloud and silicon providers, as well as industry leaders across many sectors.
About the role
We are hiring 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, you'll collaborate on an end-to-end data analytics and MLOps solution composed of popular open-source machine learning tools such as Kubeflow, MLFlow, DVC, and Feast. You may also work on workflow, ETL, data governance, and visualization tools like Apache Superset, dbt, and Temporal, or data warehouse solutions such as Apache Trino or ClickHouse.
Your team will own a solution in the analytics and machine learning space and integrate with other teams to build the world's best end-to-end data platform. These solutions may run on servers, in the cloud, on Kubernetes, on developer desktops, or as web services. We serve the needs of individuals, community members, and Global 2000/Fortune 500 customers, making our primary work available free of charge.
Responsibilities
- Develop your understanding of the entire Linux stack, from kernel, networking, and storage, 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 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
- Professional written and spoken English with excellent presentation skills
- Experience with Linux (Debian or Ubuntu preferred)
- Excellent interpersonal skills, curiosity, flexibility, and accountability
- Appreciation of diversity, politeness, and effectiveness 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
Skills
The following skills may be helpful but are not required:
- Hands-on experience with machine learning libraries or tools
- Proven track record of building highly 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 working on an open source project
Benefits
- 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
Pay
We consider geographical location, experience, and performance in shaping compensation worldwide. We revisit compensation annually (and more often for graduates and associates) to ensure we recognize outstanding performance. In addition to base pay, we offer a performance-driven annual bonus or commission.
Schedule
This initiative spans many teams that are home-based and in multiple time zones. We ensure that colleagues have company during their work hours by aligning teams broadly within the same time zone for constant collaboration and discussion.