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Software Engineer for Data Solutions
hace 2 semanas
About Canonical
">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 various sectors such as public cloud, data science, AI, engineering innovation, and IoT.
">We are hiring experienced software engineers 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 machine learning solution composed of popular, open-source tools, such as Kubeflow, MLFlow, DVC, and Feast.
">The company is founder-led, profitable, and growing. We value excellence and recruit on a global basis. Most colleagues at Canonical have worked from home since its inception in 2004.
">- 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.
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.
Additional Skills That Would Be Nice To Have:
">- 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).
