Canonical
Open Source • Cloud • AI
Canonical is the company behind Ubuntu, the world's most popular open-source operating system, which provides fast, modern, and secure Linux solutions for desktops, servers, and cloud environments. They offer a comprehensive set of products and services, including Ubuntu Desktop, Ubuntu Server, cloud solutions such as OpenStack, and tools for managing containerized applications with Kubernetes. Canonical focuses on making open-source technology reliable and accessible across various industries, from IoT and AI to enterprise infrastructure.
501 - 1000 employees
Founded 2004
Engineering Manager - MLOps & Analytics
July 2
Canonical
Open Source • Cloud • AI
Canonical is the company behind Ubuntu, the world's most popular open-source operating system, which provides fast, modern, and secure Linux solutions for desktops, servers, and cloud environments. They offer a comprehensive set of products and services, including Ubuntu Desktop, Ubuntu Server, cloud solutions such as OpenStack, and tools for managing containerized applications with Kubernetes. Canonical focuses on making open-source technology reliable and accessible across various industries, from IoT and AI to enterprise infrastructure.
501 - 1000 employees
Founded 2004
📋 Description
• Manage a distributed team of engineers and its MLOps/Analytics portfolio • Organize and lead the team’s processes in order to help it achieve its objectives • Conduct one-on-one meetings with team members • Identify and measure team health indicators • Interact with a vibrant community • Review code produced by other engineers • Attend conferences to represent Canonical and its MLOps solutions • Mentor and grow your direct reports, helping them achieve their professional goals • Work from home with global travel for 2 to 4 weeks per year for internal and external 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
🏖️ Benefits
• 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
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