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Python and Kubernetes Software Engineer- Data, Workflows, AI/ML & Analytics | WithMira

Resumen del rol

Python and Kubernetes Software Engineer- Data, Workflows, AI/ML & Analytics

Requisitos y responsabilidades

Contenido del rol extraído en secciones para revisar más rápido.

Details

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
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
Proven track record of building highly automated machine learning solutions, data pipelines, or orchestrating workflows for the cloud.
Hands-on experience with machine learning libraries, or tools.
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