Remote opportunity at
CanonicalEngineering Manager - MLOps & Analytics
Canonical seeks an Engineering Manager to guide a globally distributed team focused on MLOps and Analytics. In this position, the selected individual will lead engineering processes,…
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About This Role
Canonical seeks an Engineering Manager to guide a globally distributed team focused on MLOps and Analytics. In this position, the selected individual will lead engineering processes, mentor direct reports, review code, and collaborate closely with architects, product managers, and peers to establish ambitious product goals. The role centers on popular open-source machine learning technologies such as MLFlow, Feast, and Kubeflow, requiring a balance of technical leadership and team development. The…
Job Description
Canonical seeks an Engineering Manager to guide a globally distributed team focused on MLOps and Analytics. In this position, the selected individual will lead engineering processes, mentor direct reports, review code, and collaborate closely with architects, product managers, and peers to establish ambitious product goals. The role centers on popular open-source machine learning technologies such as MLFlow, Feast, and Kubeflow, requiring a balance of technical leadership and team development.
The successful candidate will maintain team productivity, foster a positive culture, and represent the organization at conferences and events. This position requires working from home with global travel demands of two to four weeks annually for internal and external gatherings.
Canonical is a technology enterprise recognized for publishing Ubuntu, serving as a key platform across cloud computing, IoT, and artificial intelligence. Operating as a remote-first organization since 2004, the company emphasizes fairness, global standards, and professional growth in an open-source ecosystem.
Responsibilities
- Manage a distributed team of engineers overseeing an MLOps and analytics portfolio
- Organize and lead team workflows to help members accomplish their objectives
- Conduct regular one-on-one meetings and evaluate team health indicators
- Review code written by other engineers and provide architectural leadership
- Mentor and foster the professional growth of direct reports
- Represent the organization and its MLOps solutions at conferences
- Collaborate with product managers, architects, and other engineering managers to shape the engineering roadmap
Requirements
- Proven background in professional software delivery
- Professional Python development experience, with a preference for open-source involvement
- Clear understanding of challenges and opportunities within the machine learning space
- Demonstrated experience in designing and implementing MLOps solutions
- Willingness to travel internationally up to four times per year for company events
Qualifications
- Exceptional academic history from high school and university
- Hands-on practice with machine learning tools or libraries
- Background in constructing highly automated cloud-based machine learning solutions
- Experience developing machine learning models
- Familiarity with container technologies including Docker, LXD, and Kubernetes
- Experience utilizing public cloud platforms such as AWS, Azure, and Google Cloud
- Working knowledge of Linux, open-source software, and cloud computing
- Demonstrated history of open-source contributions
Core Skills
Benefits
- Global compensation adjusted for geographical location, experience, and performance
- Annual compensation reviews
- Performance-driven annual bonus
- Personal learning and development budget of USD 2,000 per year
- Recognition rewards
- Annual holiday leave
- Maternity and paternity leave
- Employee Assistance Programme
- Priority Pass for travel and travel upgrades for long-haul company events
- Twice-yearly in-person team sprints
Frequently Asked Questions
Answers are based only on the employer’s listing; where it doesn’t say, neither do we.
Is this a remote position?
Yes, this is a globally remote role with requirements to work from home and travel internationally for two to four weeks per year.
What tools and technologies does the team use?
The team focuses on popular open-source machine learning tools including Kubeflow, MLFlow, and Feast.
What travel is expected for this role?
The position requires global travel for two to four weeks per year, including up to four trips annually for internal and external events.
What salary is offered for this role?
The source posting does not specify the salary amount.
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