Python and Kubernetes Software Engineer for Data and AI at Canonical

Confirmed open

Canonical is hiring a home-based software engineer to build open-source data, workflow, analytics and MLOps solutions with Python and Kubernetes. The team works across time zones and meets in person for company events twice a year.

Canonical

Location: Home based - Worldwide
Work arrangement: remote
Technologies: Python, AWS, Azure, Kubernetes, Docker, Linux

Role overview

This role sits in Canonical's distributed engineering teams building open-source solutions for public clouds, private infrastructure and developer machines. The work spans data analytics and MLOps, from orchestration and data pipelines to services that run on Kubernetes or conventional servers.

The employer describes the position as home-based worldwide. Team assignment considers time-zone overlap with a manager and colleagues. The posting also expects travel to company events twice a year.

Responsibilities

Design, build and maintain software that can run across public and private clouds, local workstations, servers and Kubernetes environments.
Work on end-to-end analytics and MLOps solutions using open-source tools; the posting names Kubeflow, MLflow, DVC and Feast as examples.
Contribute where needed to ETL, governance, visualisation and workflow systems, with examples including Superset, dbt, Airflow, Temporal, Trino and ClickHouse.
Develop a working understanding of Linux from the kernel, networking and storage through the application layer, alongside distributed-system topics such as observability, identity and tracing.
Debug technical problems and work openly with upstream projects and Ubuntu communities.
Exchange ideas and coordinate implementation with engineers, designers and product managers across a distributed team.

Qualifications

Professional or academic experience delivering software in Python, plus experience using Linux; Debian or Ubuntu familiarity is preferred.
A technical undergraduate degree or a persuasive account of an alternative route into engineering, together with a strong academic record as requested in the posting.
Strong written and spoken English, presentation and interpersonal skills for collaboration across a multinational team.
Evidence of personal technology projects, self-directed learning, accountability and a willingness to exchange feedback.
Ability to travel twice yearly to company events that may last up to two weeks.
Helpful but not required: automated machine-learning systems or data pipelines, workflow orchestration, ML libraries, Docker, LXD, Kubernetes, AWS, Azure, Google Cloud, software testing or open-source contributions.

Benefits

Home-based distributed work, with in-person team sprints twice a year.
A stated learning and development budget of USD 2,000 per year.
Annual compensation review, performance-linked bonus or commission, and recognition rewards; compensation depends on location, experience and performance.
Annual leave, parental leave and an employee assistance programme, subject to local benefit arrangements.
Travel opportunities for company events, including the travel benefits described in the employer posting.

About Canonical

Canonical publishes Ubuntu and builds commercial and open-source technology for cloud, data, AI and connected-device environments. The company describes itself as globally distributed and says most colleagues work from home.