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

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Canonical

πŸ“Remote - United States

Job highlights

Summary

Join Canonical's team as a Python and Kubernetes Specialist Engineer to collaborate on end-to-end data analytics and mlops solutions, working with popular open-source machine learning tools.

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

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
  • Debug issues and interact in public with upstream and Ubuntu communities
  • Generate and discuss ideas, and collaborate on finding good solutions

Benefits

  • 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

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