About Canonical

Canonical is the company behind Ubuntu, the world's most popular Linux distribution for desktops, servers, and cloud infrastructure. As a pioneering force in open source software, Canonical drives innovation in enterprise-grade solutions, powering everything from cloud-native applications to AI and machine learning workloads. With a fully remote-first culture since 2004, Canonical employs top global talent to shape the future of open source technology. Join a company committed to healthy engineering practices, community collaboration, and delivering mission-critical software to millions worldwide.

Role Overview

The Engineering Manager - MLOps & Analytics role at Canonical is a leadership position focused on guiding distributed teams in building cutting-edge machine learning operations and analytics solutions. Reporting into engineering leadership, you'll balance hands-on technical contributions with people management, ensuring your team delivers high-impact open source projects. Fluent in Python and tools like Kubeflow, MLFlow, and Feast, you'll foster a culture of excellence while collaborating with product managers and architects to define roadmaps. This globally remote role offers the flexibility to work from anywhere, with occasional travel for team sprints and conferences.

Key Focus Areas

Your work will center on MLOps pipelines, analytics platforms, and integrating ML into Ubuntu's ecosystem, leveraging Canonical's expertise in Kubernetes, cloud, and Linux.

Key Responsibilities

As Engineering Manager, you'll lead by example, combining technical depth with managerial acumen:

• Manage a distributed team handling MLOps and Analytics portfolios, ensuring focus and productivity.
• Organize processes, conduct 1:1s, and mentor engineers toward professional growth.
• Perform code reviews, provide architectural guidance, and champion quality, documentation, and performance.
• Measure team health, reflect on strategy, and unblock delivery in collaboration with stakeholders.
• Represent Canonical at conferences, engage with the open source community, and travel 2-4 weeks yearly for events.

Qualifications & Requirements

Canonical seeks proven leaders with deep technical expertise:

• Track record of professional software delivery and Python development, ideally in open source.
• Strong understanding of machine learning ecosystems, MLOps challenges, and solutions like Kubeflow, MLFlow, Feast.
• Experience designing/implementing MLOps for cloud environments.
• Exceptional academic background from high school and university.
• Comfort with distributed teams, container tech (Docker, Kubernetes), public clouds (AWS, Azure, GCP), and Linux.

Nice-to-haves include hands-on ML model building, automated cloud ML solutions, and demonstrated open source contributions.

Benefits & Perks

Canonical offers competitive, performance-based compensation reviewed annually, plus:

• Fully distributed remote work with in-person sprints twice yearly.
• USD 2,000 annual learning budget for conferences and development.
• Performance-driven bonuses, recognition rewards, and generous holiday/maternity/paternity leave.
• Employee Assistance Programme and Priority Pass for travel to global events.
• Opportunities to explore new locations while meeting colleagues worldwide.

Career Growth

At Canonical, Engineering Managers advance through technical leadership tracks or broader management roles. With mentorship, code review practices, and exposure to Ubuntu's vast ecosystem, you'll grow alongside a team passionate about open source. Annual reviews ensure recognition of outstanding contributions, positioning you for impact in AI/ML and cloud-native technologies.

Why Join Canonical

Work on Ubuntu, the backbone of open source infrastructure, in a remote-first environment that values work-life balance and innovation. Canonical's commitment to fair management, healthy practices, and community engagement sets it apart. Lead MLOps initiatives that power real-world ML at scale, contribute to global open source projects, and enjoy perks tailored for high performers. This is your chance to shape the future of machine learning on Linux.

Role FAQs

Q: Is this role fully remote? Yes, it's globally remote with 2-4 weeks travel per year for sprints and events.

Q: What tools does the team use? Python, Kubeflow, MLFlow, Feast, Kubernetes, Docker, and major clouds.

Q: What's the experience level required? Proven software delivery, MLOps design, and Python expertise; open source preferred.

Q: How does Canonical support professional growth? Through 1:1s, USD 2,000 learning budget, mentorship, and annual reviews.

Q: What's the company culture like? Remote-first since 2004, focused on high-performing teams, open source, and Ubuntu innovation.