Python and Kubernetes Software Engineer - Data, AI/ML & Analytics
location_onApollo Burger, 379, Main Street, Downtown, Salt Lake City, Salt Lake County, Utah, 84111, United States
Job Description
About Canonical
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.
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 on the team, 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.
We serve the needs of individuals and community members as much as the needs of our Global 2000 and Fortune 500 customers; we make our primary work available free of charge and our Pro subscriptions are also available to individuals for personal use at no cost. Our goal is to enable more people to enjoy the benefits of open source, regardless of their circumstances.
Location and Collaboration
This initiative spans many teams that are home-based and in multiple time zones. We believe in distributed collaboration but we also try to ensure that colleagues have company during their work hourse! Successful candidates will join a team where most members and your manager are broadly in the same time zone so that you have the benefits of constant collaboration and discussion.
Equal Opportunity
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.
Work location
Work model: Remote
Apollo Burger, 379, Main Street, Downtown, Salt Lake City, Salt Lake County, Utah, 84111, United States
Salt Lake City, Utah
Key Responsibilities
- check_circleDesign, build and maintain data analytics and MLOps solutions
- check_circleDevelop understanding of the entire Linux stack
- check_circleCollaborate with distributed teams of engineers and product managers
- check_circleDebug issues and interact with upstream and Ubuntu communities
- check_circleGenerate and discuss ideas to find good solutions
Requirements
- verifiedProfessional or academic software delivery using Python
- verifiedExceptional academic track record from high school and university
- verifiedUndergraduate degree in technical subject or compelling narrative alternative path
- verifiedProfessional written and spoken English with excellent presentation skills
- verifiedExperience with Linux (Debian or Ubuntu preferred)
- verifiedAbility to travel twice a year for company events up to two weeks long
Benefits & Perks
Similar Job Opportunities
Skills, education and keywords
Skills: python, kubernetes, linux, debian, ubuntu, docker, lxd, aws, azure, google cloud.
Education: Undergraduate degree in a technical subject; Exceptional academic track record from both high school and university.