[All remote jobs](https://jobicy.com/jobs.md)[![Canonical logo](https://jobicy.com/data/server-nyc0409/galaxy/mercury/2025/06/b4d068a9-221-1.png)](https://jobicy.com/company/canonical-ltd.md)[Canonical](https://jobicy.com/company/canonical-ltd.md) # Engineering Manager – MLOps & Analytics AI Summary Canonical is hiring an Engineering Manager to lead a distributed team responsible for an MLOps and analytics portfolio. The manager will combine people leadership, technical direction, code review, architectural guidance, and roadmap delivery. The role requires strong Python and software-delivery experience, along with practical knowledge of machine learning platforms such as Kubeflow, MLflow, and Feast. It is a globally remote position with periodic travel for internal and external events, including conferences and team sprints.[Apply for this job](#job-application)[View company](https://jobicy.com/company/canonical-ltd.md)ShareRemote from🌐 AnywhereSalaryUndisclosedDepartment[Software Engineering](https://jobicy.com/categories/engineering.md)EmploymentFull TimeExperienceSeniorPublished12 Nov 2026Apply before12 Dec 2026Listing views31Application actions1Application toolkit ## Make your next move. Prepare your resume, explore your fit, and draft a cover letter for this opportunity. Opportunity details ## About this role. The role of an Engineering Manager at [Canonical](https://jobicy.com/company/canonical-ltd.md) 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. What your day will look like * 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 What we are looking for in you * 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 Additional skills that you might also bring The following skills may be helpful to you in the role, but we don’t expect everyone to bring all of them. * Hands-on experience with machine learning libraries, or tools. * Proven track record of building highly automated machine learning solutions for the cloud. * Experience with building machine learning models * Experience with container technologies (Docker, LXD, Kubernetes, etc.) * Experience with public clouds (AWS, Azure, Google Cloud) * Experience in the Linux and open-source software world * Working knowledge of cloud computing * Passionate about software quality and testing * Experience working on a distributed team on an open source project — even if that is community open source contributions. * Demonstrated track record of Open Source contributions What we offer you 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 About Canonical Canonical is a pioneering tech firm that is at the forefront of the global move to open source. As the company that publishes Ubuntu, one of the most important open source projects and the platform for AI, IoT and the cloud, we are changing the world on a daily basis. We recruit on a global basis and set a very high standard for people joining the company. We expect excellence – in order to succeed, we need to be the best at what we do. Canonical has been a remote-first company since its inception in 2004.​ Work at Canonical is a step into the future, and will challenge you to think differently, work smarter, learn new skills, and raise your game. Canonical provides a unique window into the world of 21st-century digital business. Canonical is an equal opportunity employer We are proud to foster a workplace free from discrimination. Diversity of experience, perspectives, and background create a better work environment and better products. [Whatever your identity, we will give your application fair consideration.](https://canonical.com/careers/diversity/identity) #LI-remote Show more [Apply now >](https://jobicy.com/jobs/161669-engineering-manager-mlops-analytics-2.md) > Annual salary information is not provided for this position. Explore salary ranges for similar roles in our [Salary Directory ›](https://jobicy.com/salaries.md) * ![Upload CV](data:image/svg+xml;base64,PHN2ZyB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciIHdpZHRoPSI2NSIgaGVpZ2h0PSI2NSIgZmlsbD0ibm9uZSIgeG1sbnM6dj0iaHR0cHM6Ly92ZWN0YS5pby9uYW5vIj48ZyBjbGlwLXBhdGg9InVybCgjQSkiPjxwYXRoIGQ9Ik0wIDBINjVWNjVIMFYwWiIgZmlsbD0iIzAyOWFlYiIvPjxnIGZpbGw9IiNmZmYiIHN0cm9rZT0iI2ZmZiIgc3Ryb2tlLXdpZHRoPSIyIj48cGF0aCBkPSJNMzMuMDQ5IDE1LjQ1NGExLjQzIDEuNDMgMCAwIDAtMi4wOTcgMGwtNy41NzkgOC4xNDdhMS4zOCAxLjM4IDAgMCAwIC4wOSAxLjk3MyAxLjQ0IDEuNDQgMCAwIDAgMi4wMDgtLjA4OGw1LjEwOS01LjQ5MnYyMC42MWExLjQxIDEuNDEgMCAwIDAgMS40MjEgMS4zOTdjLjc4NSAwIDEuNDIxLS42MjUgMS40MjEtMS4zOTd2LTIwLjYxbDUuMTA5IDUuNDkyYTEuNDQgMS40NCAwIDAgMCAyLjAwOC4wODggMS4zOCAxLjM4IDAgMCAwIC4wOS0xLjk3M2wtNy41NzktOC4xNDZ6TTE2Ljc2OSAzOC40YzAtLjc3My0uNjItMS40LTEuMzg1LTEuNFMxNCAzNy42MjcgMTQgMzguNHYuMTAybC4yMTUgNi4yMjljLjIyMyAxLjY4LjcwMSAzLjA5NSAxLjgxMyA0LjIxOHMyLjUxIDEuNjA3IDQuMTcyIDEuODMzYzEuNi4yMTggMy42MzYuMjE4IDYuMTYuMjE4aDExLjI4bDYuMTYtLjIxOGMxLjY2Mi0uMjI2IDMuMDYxLS43MDkgNC4xNzItMS44MzNzMS41ODktMi41MzggMS44MTMtNC4yMThDNTAgNDMuMTEzIDUwIDQxLjA1NSA1MCAzOC41MDNWMzguNGMwLS43NzMtLjYyLTEuNC0xLjM4NS0xLjRzLTEuMzg1LjYyNy0xLjM4NSAxLjRsLS4xOSA1Ljk1OGMtLjE4MiAxLjM3LS41MTUgMi4wOTUtMS4wMjYgMi42MTJzLTEuMjI4Ljg1My0yLjU4MyAxLjAzOGMtMS4zOTUuMTktMy4yNDMuMTkzLTUuODkzLjE5M0gyNi40NjJjLTIuNjUgMC00LjQ5OC0uMDAzLTUuODkzLS4xOTMtMS4zNTUtLjE4NC0yLjA3Mi0uNTIxLTIuNTgzLTEuMDM4cy0uODQ0LTEuMjQyLTEuMDI2LTIuNjEyYy0uMTg3LTEuNDEtLjE5MS0zLjI3OS0uMTkxLTUuOTU4eiIvPjwvZz48L2c+PGRlZnM+PGNsaXBQYXRoIGlkPSJBIj48cGF0aCBmaWxsPSIjZmZmIiBkPSJNMCAwaDY1djY1SDB6Ii8+PC9jbGlwUGF0aD48L2RlZnM+PC9zdmc+) ### Upload your resume now To unlock remote work opportunities and be discovered by global employers. This job listing has been manually reviewed by the Jobicy Trust & Safety Team for compliance with our posting guidelines, including verification of the company's legitimacy, accuracy of job details, clarity of remote work policy, and absence of misleading or fraudulent content. ## Role DNA A quick view of the complexity, pace, ownership and collaboration implied by the job description. ### Job Complexity 5/5EasyHard ### Pace & Pressure 4/5RelaxedFast-paced ### Autonomy Level 5/5GuidedFull ownership ### Communication Load 5/5IndependentCollaborative AI insightThis is a senior leadership role requiring both deep MLOps expertise and the ability to develop, manage, and align a distributed engineering team. Success depends on balancing technical quality, delivery execution, stakeholder alignment, and team health. ## Salary analysis Estimated compensation compared with the broader US market for similar roles. Estimated job median (per year)Market rate$165,000US market range (per year)$140k–$210k0$231.00k AI insightThe yearly pay period is inferred from the job context; it was not explicitly stated by the employer. No employer base-salary amount is disclosed. The yearly cadence is inferred from the permanent engineering-management context and annual compensation review; the displayed figures are estimated USD annual-market compensation for a senior MLOps Engineering Manager. ## Core skills Skills and capabilities most closely associated with this opportunity. [Engineering Management](https://jobicy.com/jobs?search_keywords=Engineering%20Management.md)[MLOps](https://jobicy.com/jobs?search_keywords=MLOps.md)[Machine Learning](https://jobicy.com/jobs?search_keywords=Machine%20Learning.md)[Python](https://jobicy.com/jobs?search_keywords=Python.md)[Kubeflow](https://jobicy.com/jobs?search_keywords=Kubeflow.md)[MLflow](https://jobicy.com/jobs?search_keywords=MLflow.md)[Feast](https://jobicy.com/jobs?search_keywords=Feast.md)[Software Architecture](https://jobicy.com/jobs?search_keywords=Software%20Architecture.md)[Code Review](https://jobicy.com/jobs?search_keywords=Code%20Review.md)[People Management](https://jobicy.com/jobs?search_keywords=People%20Management.md)[Cloud Computing](https://jobicy.com/jobs?search_keywords=Cloud%20Computing.md)[Kubernetes](https://jobicy.com/jobs?search_keywords=Kubernetes.md)[Docker](https://jobicy.com/jobs?search_keywords=Docker.md)[Open Source](https://jobicy.com/jobs?search_keywords=Open%20Source.md)[Technical Roadmapping](https://jobicy.com/jobs?search_keywords=Technical%20Roadmapping.md) Sample interview questionsHow would you establish effective operating practices for a distributed MLOps engineering team?I would set clear team objectives, define measurable delivery and reliability indicators, and maintain regular one-on-ones, planning sessions, and retrospectives. I would also document decisions and ensure that asynchronous communication supports colleagues across time zones. How do you balance people management with hands-on technical leadership? I focus first on creating the conditions for the team to succeed: clear priorities, coaching, and removal of blockers. I remain technically engaged through design reviews, code reviews, and architecture discussions, while avoiding becoming a bottleneck for execution. What factors would you consider when designing an MLOps platform? I would consider reproducibility, experiment tracking, feature management, model versioning, deployment automation, observability, security, and governance. The design should fit the users' workflows and integrate cleanly with the organization's cloud and data platforms. How would you improve software quality in an open-source MLOps project? I would establish practical quality standards around automated testing, code review, documentation, performance monitoring, and release discipline. I would also encourage early community feedback and use incidents or defects as inputs for improving engineering practices. Describe how you would handle competing roadmap priorities from product managers, architects, and the engineering team. I would make the trade-offs explicit by evaluating customer impact, technical risk, strategic alignment, team capacity, and dependencies. I would facilitate a shared prioritization discussion, document the decision, and communicate the resulting roadmap and rationale clearly. Next step ## Apply now. Follow the employer’s application method and review Jobicy’s safety guidance before sharing personal information. 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