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- Tasks: Join a team to develop cutting-edge data analytics and machine learning solutions using Python and Kubernetes.
- Company: Canonical is a leading open source software provider, known for Ubuntu and innovative tech solutions.
- Benefits: Enjoy remote work, a personal development budget, annual bonuses, and opportunities to travel globally.
- Why this job: Be part of a pioneering company that values collaboration, diversity, and open source technology.
- Qualifications: A strong academic background in tech or relevant experience, with a passion for software and problem-solving.
- Other info: Work in a fully distributed environment with a focus on continuous learning and professional growth.
The predicted salary is between 28800 - 48000 £ per year.
Python and Kubernetes Software Engineer – Data, AI/ML & Analytics
Join to apply for the Python and Kubernetes Software Engineer – Data, AI/ML & Analytics role at Canonical
Python and Kubernetes Software Engineer – Data, AI/ML & Analytics
Join to apply for the Python and Kubernetes Software Engineer – Data, AI/ML & Analytics role at 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. 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: 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.
What your day will look like
- Develop your understanding of the entire Linux stack, from kernel, networking, and storage, to the application layer
- Design, build and maintain solutions that will be deployed on public and private clouds and local workstations
- Master distributed systems concepts such as observability, identity, tracing
- Work with both Kubernetes and machine-oriented open source applications
- Collaborate proactively with a distributed team of engineers, designers and product managers
- Debug issues and interact in public with upstream and Ubuntu communities
- Generate and discuss ideas, and collaborate on finding good solutions
What we are looking for in you
- Professional or academic software delivery using Python
- Exceptional academic track record from both high school and university
- Undergraduate degree in a technical subject or a compelling narrative about your alternative chosen path
- Confidence to respectfully speak up, exchange feedback, and share ideas without hesitation
- Track record of going above-and-beyond expectations to achieve outstanding results
- Passion for technology evidenced by personal projects and initiatives
- The work ethic and confidence to shine alongside motivated colleagues
- Professional written and spoken English with excellent presentation skills
- Experience with Linux (Debian or Ubuntu preferred)
- Excellent interpersonal skills, curiosity, flexibility, and accountability
- Appreciative of diversity, polite and effective in a multi-cultural, multi-national organisation
- Thoughtfulness and self-motivation
- Result-oriented, with a personal drive to meet commitments
- Ability to travel twice a year, for company events up to two weeks long
Additional Skills That Would Be Nice To Have
The following skills may be helpful to you in the role, but we don\’t expect everyone to bring all of them.
- Hands-on experience with machine learning libraries, or tools.
- Proven track record of building highly automated machine learning solutions for the cloud.
- Experience with container technologies (Docker, LXD, Kubernetes, etc.)
- Experience with public clouds (AWS, Azure, Google Cloud)
- Working knowledge of cloud computing
- Passionate about software quality and testing
- Experience working on an open source project
What we offer colleagues
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 or commission. 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 2,000 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
About Canonical
Canonical is a pioneering tech firm at the forefront of the global move to open source. As the company that publishes Ubuntu, one of the most important open source projects and the platform for AI, IoT and the cloud, we are changing the world of software. We recruit on a global basis and set a very high standard for people joining the company. We expect excellence – in order to succeed, we need to be the best at what we do. Most colleagues at Canonical have worked from home since its inception in 2004. Working here is a step into the future, and will challenge you to think differently, work smarter, learn new skills, and raise your game.
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.
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Python and Kubernetes Software Engineer - Data, AI/ML & Analytics employer: Canonical
Contact Detail:
Canonical Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Python and Kubernetes Software Engineer - Data, AI/ML & Analytics
✨Tip Number 1
Familiarise yourself with the latest trends in Python and Kubernetes, especially in relation to data analytics and machine learning. Being able to discuss recent developments or tools like Kubeflow and MLFlow during your interview can really set you apart.
✨Tip Number 2
Engage with the open-source community by contributing to projects related to AI/ML or Kubernetes. This not only enhances your skills but also demonstrates your passion and commitment to potential employers like us at Canonical.
✨Tip Number 3
Prepare to showcase any personal projects that involve Python, Kubernetes, or data analytics. Having tangible examples of your work can help illustrate your capabilities and enthusiasm for the role.
✨Tip Number 4
Network with current employees or alumni from Canonical on platforms like LinkedIn. Gaining insights into the company culture and expectations can give you a significant advantage during the interview process.
We think you need these skills to ace Python and Kubernetes Software Engineer - Data, AI/ML & Analytics
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience with Python, Kubernetes, and any machine learning projects. Use specific examples that demonstrate your skills and achievements in these areas.
Craft a Compelling Cover Letter: In your cover letter, express your passion for open source software and how your background aligns with Canonical's mission. Mention any personal projects or initiatives that showcase your technical skills and enthusiasm.
Showcase Your Technical Skills: Include a section in your application that lists your technical skills, particularly those related to Linux, cloud computing, and machine learning tools. Be specific about your experience with technologies like Docker, AWS, or Kubeflow.
Prepare for Potential Questions: Think about the types of questions you might be asked during an interview. Prepare to discuss your previous projects, your approach to problem-solving, and how you collaborate with remote teams.
How to prepare for a job interview at Canonical
✨Showcase Your Python Skills
Be prepared to discuss your experience with Python in detail. Highlight specific projects where you've used Python, especially in data analytics or machine learning contexts. Demonstrating your understanding of libraries like Pandas, NumPy, or TensorFlow can set you apart.
✨Familiarise Yourself with Kubernetes
Since the role involves Kubernetes, make sure you understand its architecture and how it works with containerised applications. Be ready to discuss your hands-on experience with deploying applications on Kubernetes and any challenges you've faced.
✨Understand Open Source Principles
Canonical is a leader in open source, so it's crucial to show your passion for open source software. Discuss any contributions you've made to open source projects or how you've used open source tools in your work. This will demonstrate your alignment with the company's values.
✨Prepare for Collaborative Scenarios
Given the distributed nature of the team, be ready to talk about your experience working in remote teams. Share examples of how you've effectively communicated and collaborated with colleagues across different time zones, as this will be key in your role.