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Engineering Manager - MLOps Analytics

Canonical
Remote
Full Time
Posted September 18, 2025
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Job Description

An Engineering Manager at Canonical leads and develops a remote engineering team focused on MLOps and open-source machine learning tools, ensuring technical excellence, team growth, and effective collaboration to deliver innovative AI and cloud solutions.

Key Responsibilities

  • Manage a distributed team of engineers and oversee the MLOps Analytics portfolio
  • Organize and lead team processes to achieve objectives
  • Conduct one-on-one meetings and measure team health indicators
  • Review code and provide architectural leadership
  • Mentor and develop team members to achieve professional growth
  • Collaborate with other managers, product managers, and architects to produce an engineering roadmap
  • Ensure high-quality engineering practices, documentation, and performance optimization
  • Represent Canonical and its solutions at conferences and community events

Requirements

  • A proven track record of professional experience of software delivery.
  • Professional Python development experience, preferably with a track record in open source.
  • A proven understanding of the machine learning space, its challenges and opportunities to improve.
  • Experience designing and implementing MLOps solutions.
  • An exceptional academic track record from both high school and preferably university.
  • Willingness to travel up to 4 times a year for internal events.
  • Hands-on experience with machine learning libraries, or tools (optional but helpful).
  • Proven track record of building highly automated machine learning solutions for the cloud (optional but helpful).
  • Experience with building machine learning models (optional but helpful).
  • Experience with container technologies such as Docker, LXD, Kubernetes, etc. (optional but helpful).
  • Experience with public clouds AWS, Azure, Google Cloud (optional but helpful).
  • Experience in the Linux and open-source software world (optional but helpful).
  • Working knowledge of cloud computing (optional but helpful).
  • Passionate about software quality and testing (optional but helpful).
  • Experience working on a distributed team on an open source project, including community open source contributions (optional but helpful).
  • Demonstrated track record of Open Source contributions (optional but helpful).

Benefits & Perks

Compensation is based on geographical location, experience, and performance, with annual reviews and more frequent reviews for graduates and associates
Performance-driven annual bonus
Distributed work environment with twice-yearly in-person team sprints
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 for travel and travel upgrades for long haul company events

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