Software engineer on the Charmed Analytics team, building open source data, analytics and MLOps solutions with Python and Kubernetes, covering tools such as Kubeflow, MLflow, Superset and Trino on servers, clouds, developer desktops or as web services.
Develop your understanding of the entire Linux stack, from kernel, networking, and storage, to the application layer
Create, ship, and maintain solutions for public and private clouds and local workstations
Master distributed systems concepts such as observability, identity, and 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
Requirements
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
Nice to have: Track record of building highly automated machine learning solutions, data pipelines, or orchestrating workflows in the cloud
Nice to have: Hands-on experience with machine learning libraries or tools
Nice to have: Experience with container technologies such as Docker, LXD, or Kubernetes
Nice to have: Experience with public clouds (AWS, Azure, Google Cloud)
Nice to have: Working knowledge of cloud computing
Nice to have: Passion for software quality and testing
Nice to have: Experience working on an open source project
Done for you
We'll apply to this for you
Denidel's HR team submits and tracks the application on your behalf.
