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Data Driven Engineer
2 weeks ago
At Canonical, we are changing the world of software by publishing Ubuntu, one of the most important open source projects and the platform for AI, Io T, and the cloud.
About UsWe 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.
About the RoleWe 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.
You will 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.
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.
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.
Key Responsibilities:
- 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
We are looking for individuals who possess exceptional academic track records, professional or academic software delivery experience using Python, and a passion for technology evidenced by personal projects and initiatives.
A strong candidate will also demonstrate excellent interpersonal skills, curiosity, flexibility, and accountability, as well as a result-oriented mindset with a personal drive to meet commitments.
The following skills may be helpful but are not required:
- 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
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
