Engineering Manager - Kubeflow/MLOps - Python/Kubernetes

Home based - Americas, EMEA

Applications have closed

Canonical Ltd.

Canonical makes open source secure, reliable and easy to use, providing support for Ubuntu and a portfolio of enterprise-grade technologies. Founded in 2004, Canonical operates globally with team members in over 80 countries.

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Manage a team of engineers delivering a world-class machine learning operations platform that can be deployed on any Kubernetes. We're building the most robust, well-integrated and sustainable way of operating a comprehensive MLOps platform on Kubernetes, powered by Juju and Charmed Operators.

Location: Remote role for candidates in AMER and EMEA.

What your day will look like

  • Lead a world-class rigorous software engineering process
  • Lead the design and implementation of Charmed Operators
  • Collaborate with other leaders to develop best practices
  • Work with partners and the open source community
  • Coach, mentor and develop engineers across the business

What we are looking for in you

  •  Exceptional academic track record in maths and the sciences
  •  Demonstrated ability to design and build high quality software
  •  High level of proficiency in Python and with Kubernetes
  •  Demonstrated ability to build and lead engineering teams
  •  Willingness to travel up to 4 times a year for internal events

Additional skills that you might also bring

  • Experienced in Machine Learning tooling
  • Experienced in the operation of Machine Learning tooling at scale
  • Competency in Go programming
  • Experience with working in and contributing to open source communities

What we offer you

Your base pay will depend on various factors including your geographical location, level of experience, knowledge and skills. In addition to the benefits above, certain roles are also eligible for additional benefits and rewards including annual bonuses and sales incentives based on revenue or utilisation. Our compensation philosophy is to ensure equity right across our global workforce.  

In addition to a competitive base pay, we provide all team members with additional benefits, which reflect our values and ideals. Please note that additional benefits may apply depending on the work location and, for more information on these, please ask your Talent Partner.

  • Fully remote working environment - we’ve been working remotely since 2004!
  • Personal learning and development budget of 2,000USD per annum
  • Annual compensation review
  • Recognition rewards
  • Annual holiday leave
  • Parental Leave
  • Employee Assistance Programme
  • Opportunity to travel to new locations to meet colleagues at ‘sprints’
  • Priority Pass for travel and travel upgrades for long haul company events

About Canonical

Canonical is a pioneering tech firm that is at the forefront of the global move to open source. As the company that publishes Ubuntu, one of the most important open source projects and the platform for AI, IoT and the cloud, we are changing the world on a daily basis. We 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.

Canonical has been a remote-first company since its inception in 2004.​ Work at Canonical is a step into the future, and will challenge you to think differently, work smarter, learn new skills, and raise your game. Canonical provides a unique window into the world of 21st-century digital business.

Canonical is an equal opportunity employer

We are proud to foster a workplace free from discrimination. Diversity of experience, perspectives, and background create a better work environment and better products. Whatever your identity, we will give your application fair consideration.

#LI-remote 

* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰

Tags: Engineering Kubeflow Kubernetes Machine Learning MLOps Open Source Python

Perks/benefits: Career development Competitive pay Equity Parental leave Team events Travel

Regions: Remote/Anywhere Africa Europe Middle East North America South America

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