Remote opportunity at
CanonicalPython and Kubernetes Software Engineer - Data, Workflows, AI/ML & Analytics
Canonical is recruiting Python and Kubernetes engineers to build data, workflow, AI/ML and analytics solutions. This is a full-time, remote position across several time zones. Each…
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About This Role
Canonical is recruiting Python and Kubernetes engineers to build data, workflow, AI/ML and analytics solutions. This is a full-time, remote position across several time zones. Each engineer joins a team whose manager and most members work in roughly the same time zone, which makes everyday collaboration easier. The company publishes Ubuntu and supports individual community members as well as large enterprise customers, with its core work freely available. The engineer…
Job Description
Canonical is recruiting Python and Kubernetes engineers to build data, workflow, AI/ML and analytics solutions. This is a full-time, remote position across several time zones. Each engineer joins a team whose manager and most members work in roughly the same time zone, which makes everyday collaboration easier. The company publishes Ubuntu and supports individual community members as well as large enterprise customers, with its core work freely available.
The engineer helps create complete analytics and MLOps stacks, assembled from community-favoured machine learning projects including Kubeflow, MLflow, DVC and Feast. The team also works with ETL, data governance and visualisation tools like Apache Superset and dbt, workflow orchestration using Airflow and Temporal, and data warehouses such as Trino and ClickHouse. Solutions might run on servers, in the cloud, on developer machines or as web services.
Day to day, the engineer builds a working grasp of Linux, covering the kernel, networking, storage and application layers, and designs, builds and maintains solutions for public and private clouds and developer workstations. The role involves pairing Kubernetes work with open source tools built for machine operations, studying distributed-systems topics like observability, identity and tracing, and debugging issues in public alongside upstream and Ubuntu communities. Engineers also brainstorm ideas with designers and product managers to reach sound solutions.
Applicants should have professional or academic software delivery experience with Python, and an excellent academic track record or a convincing alternative route. They need to speak up confidently, exchange feedback openly, and bring ideas to the table. Strong English writing and speaking, presentation skills, interest in Linux (Debian or Ubuntu preferred), and self-motivation are expected. Nice-to-haves include automated ML pipeline or workflow orchestration work, ML libraries, containers, public cloud platforms, a focus on software quality and testing, and contributions to open source projects. Pay depends on location, experience and performance.
Responsibilities
- Design, build and maintain solutions for public and private clouds and workstations
- Pair Kubernetes work with open source tools built for machine operations
- Develop understanding of the Linux stack from kernel to application layer
- Study distributed systems concepts like observability, identity and tracing
- Troubleshoot problems openly alongside upstream and Ubuntu contributors
- Collaborate with engineers, designers and product managers on solutions
Requirements
- Professional or academic software delivery experience using Python
- Confidence to speak up, share feedback and exchange ideas
- Record of exceeding targets and delivering excellent outcomes
- Strong English writing and speaking, with presentation skills
- Linux background (Debian or Ubuntu a plus)
- Readiness to fly abroad twice a year at company gatherings
Qualifications
- Technical undergraduate qualification, or a well-argued alternative route
- Experience building automated ML solutions, data pipelines or workflow orchestration (nice to have)
- Hands-on work with ML toolkits (nice to have)
- Experience with container tools such as Docker, LXD or Kubernetes (nice to have)
- Experience with public clouds such as AWS, Azure or Google Cloud (nice to have)
- Contributions to an open source project (nice to have)
Core Skills
Benefits
- Performance-linked annual bonus or commission
- USD 2,000 yearly learning budget
- Annual pay review and recognition awards
- Holiday, maternity and paternity leave, and an employee assistance programme
- Two in-person team sprints per year and visits to new locations
- Priority Pass and upgrades on long-haul company travel
Frequently Asked Questions
Answers are based only on the employer’s listing; where it doesn’t say, neither do we.
Is this Python and Kubernetes engineer role remote?
Yes. The role is listed as remote, and teams are spread across several time zones.
What technologies does the team use?
The posting mentions Kubeflow, MLflow, DVC, Feast, Apache Superset, dbt, Airflow, Temporal, Trino and ClickHouse, with Python and Kubernetes as core skills.
Is a salary figure stated?
No specific salary is listed. Base pay depends on location, experience and performance.
Does the role involve travel?
Yes. The posting asks for the readiness to fly abroad twice a year at company gatherings of up to two weeks.
Sample Interview Questions
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