About the Job:
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 key enterprise initiatives, including public cloud, data science, AI, engineering innovation, and IoT. The company operates with over 1000 colleagues in 70+ countries, emphasizing a globally distributed collaboration model.
We are looking for 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. Your role will involve collaborating on end-to-end data analytics and MLOps solutions, utilizing popular open-source machine learning tools such as Kubeflow, MLFlow, DVC, and Feast. Additionally, you may work with ETL, data governance, visualization tools like Apache SuperSet or dbt, and workflow orchestration tools such as Airflow and Temporal.
Your day will include:
- Developing an understanding of the entire Linux stack, from kernel to application layer.
- Designing, building, and maintaining solutions for public/private clouds and local workstations.
- Mastering distributed systems concepts such as observability and tracing.
- Collaborating proactively with a distributed team of engineers, designers, and product managers.
- Debugging issues and contributing to upstream and Ubuntu communities.
Requirements:
- Professional or academic software delivery using Python.
- Exceptional academic track record, with an undergraduate degree in a technical subject or a compelling narrative about an alternative path.
- Confidence to exchange feedback and share ideas openly.
- A track record of exceeding expectations.
- Passion for technology, evidenced by personal projects.
- Professional written and spoken English with excellent presentation skills.
- Experience with Linux (Debian or Ubuntu preferred).
- Excellent interpersonal skills, curiosity, flexibility, and accountability.
Additional Skills (nice to have):
- Proven experience in building automated machine learning solutions or data pipelines.
- Hands-on experience with machine learning libraries or tools.
- Familiarity with container technologies (Docker, Kubernetes).
- Experience with public clouds (AWS, Azure, Google Cloud).
- A passion for software quality and testing.
- Prior experience working on open-source projects.
Compensation and Benefits:
Canonical considers various factors when determining compensation, including geographical location and performance. In addition to base pay, we offer performance-driven bonuses and a personal learning and development budget of USD 2,000 per year. Additional benefits include:
- Distributed work environment with in-person team events twice a year.
- Annual compensation reviews.
- Recognition rewards.
- Paid annual leave, maternity, and paternity leave.
- Employee Assistance Programme.
- Opportunities to travel for company events.
Canonical is a pioneering tech firm focused on open source innovation, and we are proud to foster a diverse and inclusive workplace. All applications will be considered fairly without discrimination.
