National AI Awards 2025Discover AI's trailblazers! Join us to celebrate innovation and nominate industry leaders.

Nominate & Attend

Software Engineer - Python - Container Images

Canonical
London
9 months ago
Applications closed

Related Jobs

View all jobs

Software Manager

Software Engineer III - Data Engineer - Python, SQL - Senior Associate

Software Engineer II - Data Engineer, Python, SQL - Associate

Senior Software Engineer – API & ML Infrastructure

Junior Embedded Software Engineer

Lead Python Software Engineer

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 + colleagues in 75+ countries and very few office based roles. 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.

Canonical is building a new generation of Ubuntu-based container images to simplify open-source application deployment across the world. These container images will be free to use with long-term security commitments, and engineered for performance, security and usability. As with Ubuntu, we will work in the open and welcome community participation.

In this role, you’ll be developing the tools and technology for building and maintaining this new generation of container images. You’ll be working with multiple teams, both inside and outside Canonical, to ensure we deliver container images with the highest quality whilst maintaining a seamless Ubuntu user experience. You will also be highly involved in the implementation and maintenance of the Continuous Integration and Continuous Delivery automation around these container images, for which you are expected to demonstrate deep insights into container-based DevOps.

You will be contributing to fast-moving products like Rocks () and Chisel, and thus have the chance to help steer and consolidate this new team. You’ll gain experience with numerous container technologies and participate in exciting and exploratory tasks, where your feedback will be critical for the decision-making process. As an engineer, your seniority will be based on your software development background and ability to lead junior team members.

Come build a rewarding, meaningful career working with the best and brightest people in technology at Canonical. This is an exciting opportunity for experienced software engineers looking for a place to leave their mark, who are passionate about shaping an open source product with the highest quality, with and for the community!

**Location**: EMEA 

This role entails

Build robust, scalable, leading-edge container images Work on automated Ci/CD processes for building, testing and publishing our container images Write tools and tests for assessing security compliance and cloud-native compatibility Work in Python to deliver new functionalities to our container-building tools Participate in strong engineering process through code and architectural review Provide technical feedback for the team’s decision-making process Engage with the open-source community as a subject-matter expert Grow our knowledge base and write documentation Work in a collaborative, agile and globally distributed environment Mentor and help hiring Work from home with global travel up to 15% for internal and external events

What we are looking for in you

You are knowledgeable and passionate about software development You are a team player and have experience in collaborative development You have worked with CI/CD systems (e.g. Jenkins, GitHub Actions, Concourse CI, etc.) You have a track record of delivering timely, high-quality software You have experience with container images and containerised operations You master at least one container management/orchestration tool (e.g. Docker, Kubernetes, etc.) You have significant experience with Python You are experienced with Linux systems administration and package management You have strong written and verbal communication skills to convey technical concepts You bring clarity to technical and engineering discussions You are someone who strongly believes that sharing is caring, and knowledge is power Your skills range from those of a Graduate to a mid-senior Software Engineer You have a Bachelor’s or equivalent in Computer Science, STEM or a similar degree

What we offer you

We consider geographical location, experience, and performance in shaping compensation worldwide. We revisit compensation annually (and more often for graduates and associates) to ensure we recognise outstanding performance. In addition to base pay, we offer a performance-driven annual bonus. We provide all team members with additional benefits, which reflect our values and ideals. We balance our programs to meet local needs and ensure fairness globally.

Distributed work environment with twice-yearly team sprints in person Personal learning and development budget of USD 2, per year Annual compensation review Recognition rewards Annual holiday leave Maternity and paternity leave Employee Assistance Programme Opportunity to travel to new locations to meet colleagues Priority Pass, and travel upgrades for long haul company events
National AI Awards 2025

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Return-to-Work Pathways: Relaunch Your Machine Learning Career with Returnships, Flexible & Hybrid Roles

Returning to work after an extended break can feel like starting from scratch—especially in a specialist field like machine learning. Whether you paused your career for parenting, caring responsibilities or another life chapter, the UK’s machine learning sector now offers a variety of return-to-work pathways. From structured returnships to flexible and hybrid roles, these programmes recognise the transferable skills and resilience you’ve developed, pairing you with mentorship, upskilling and supportive networks to ease your transition back. In this guide, you’ll discover how to: Understand the current demand for machine learning talent in the UK Leverage your organisational, communication and analytical skills in ML contexts Overcome common re-entry challenges with practical solutions Refresh your technical knowledge through targeted learning Access returnship and re-entry programmes tailored to machine learning Find roles that fit around family commitments—whether flexible, hybrid or full-time Balance your career relaunch with caring responsibilities Master applications, interviews and networking specific to ML Learn from inspiring returner success stories Get answers to common questions in our FAQ section Whether you aim to return as an ML engineer, research scientist, MLOps specialist or data scientist with an ML focus, this article will map out the steps and resources you need to reignite your machine learning career.

LinkedIn Profile Checklist for Machine Learning Jobs: 10 Tweaks to Drive Recruiter Interest

The machine learning landscape is rapidly evolving, with demand soaring for experts in modelling, algorithm tuning and data-driven insights. Recruiters hunt for candidates proficient in Python, TensorFlow, PyTorch and MLOps processes. A generic profile simply won’t cut it. Our step-by-step LinkedIn for machine learning jobs checklist covers 10 targeted tweaks to ensure your profile ranks in searches and communicates your technical impact. Whether launching your ML career or seeking leadership roles, these optimisations will sharpen your professional narrative and boost recruiter engagement.

Part-Time Study Routes That Lead to Machine Learning Jobs: Evening Courses, Bootcamps & Online Masters

Machine learning—a subset of artificial intelligence—enables computers to learn from data and improve over time without explicit programming. From predictive maintenance in manufacturing to recommendation engines in e-commerce and diagnostic tools in healthcare, machine learning (ML) underpins many of today’s most innovative applications. In the UK, demand for ML professionals—engineers, data scientists, research scientists and ML operations specialists—is growing rapidly, with roles projected to increase by over 50% in the next five years. However, many aspiring ML practitioners cannot step away from work or personal commitments for full-time study. Thankfully, a rich ecosystem of part-time learning pathways—Evening Courses, Intensive Bootcamps and Flexible Online Master’s Programmes—empowers you to learn machine learning while working. This comprehensive guide examines each route: foundational CPD units, immersive bootcamps, accredited online MSc programmes, funding options, planning strategies and a real-world case study. Whether you’re a software developer branching into ML, a statistician aiming to upskill, or a professional exploring AI-driven innovation, you’ll discover how to build in-demand ML expertise on your own schedule.