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

Canonical is seeking Python and Kubernetes Specialist Engineers focused on Data, AI/ML and Analytics Solutions to join their 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 from the analytics and machine learning space, and integrate with the solutions from other teams to build the world's best end-to-end data platform. These solutions may be run on servers or on the cloud, on machines or on Kubernetes, on developer desktops, or as web services.

Key responsibilities include:

• Developing understanding of the entire Linux stack
• Designing, building, and maintaining solutions for public and private clouds and local workstations
• Mastering distributed systems concepts
• Working with Kubernetes and machine-oriented open source applications
• Collaborating with a distributed team
• Debugging issues and interacting with upstream and Ubuntu communities
• Generating and discussing ideas for solutions

Requirements:

• Professional or academic software delivery using Python or Golang
• Exceptional academic track record
• Undergraduate degree in a technical subject (or equivalent experience)
• Strong communication and interpersonal skills
• Passion for technology
• Experience with Linux (Debian or Ubuntu preferred)
• Ability to travel twice a year for company events

Canonical offers a distributed work environment, personal learning and development budget, annual compensation review, and various benefits. The company values diversity and fosters a workplace free from discrimination.