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 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.