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  3. Engineering Manager - MLOps & Analytics
CA

Engineering Manager - MLOps & Analytics

Canonical
Remote
Full Time
Posted November 22, 2024
$114k - $174k· Est.
Power Generation
Remote
~32 people viewed this recently
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Application opens on company website

Job Description

The following skills may be helpful to you in the role, but we don't expect everyone to bring all of them.

Key Responsibilities

  • As an Engineering Manager at Canonical, you must be technically strong, but your main responsibility is to run an effective team and develop the colleagues you manage. You will develop and review code as a leader, while at the same time staying aware of that the best way to improve the product is to ensure that the whole team is focused, productive and unblocked.
  • You are expected to help them grow as engineers, do meaningful work, do it outstandingly well, find professional and personal satisfaction, and work well with colleagues and the community. You will also be expected to be a positive influence on culture, facilitate technical delivery, and regularly reflect with your team on strategy and execution.
  • You will collaborate closely with other Engineering Managers, product managers, and architects, producing an engineering roadmap with ambitious and achievable goals.
  • We expect Engineering Managers to be fluent in the programming language, architecture, and components that their team uses, in this case popular open-source machine learning tools like Kubeflow, MLFlow, and Feast.
  • Code reviews and architectural leadership are part of the job. The commitment to healthy engineering practices, documentation, quality and performance optimisation is as important, as is the requirement for fair and clear management, and the obligation to ensure a high-performing team.
  • Location: This is a Globally remote role.

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

Benefits & Perks

  • We consider geographical location, experience, and performance in shaping compensation worldwide. We revisit compensation annually (and more often for graduates and associates) to ensure we recognise outstanding performance. In addition to base pay, we offer a performance-driven annual bonus. We provide all team members with additional benefits, which reflect our values and ideals. We balance our programs to meet local needs and ensure fairness globally.
  • Distributed work environment with twice-yearly team sprints in person - we’ve been working remotely since 2004!
  • 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 from your team and others
  • Priority Pass for travel and travel upgrades for long haul company events

Ready to Apply?

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