Engineering Manager – MLOps & Analytics

Remote from
🌐 Anywhere
Annual salary
Undisclosed
Salary information is not provided for this position. Check our Salary Directory to estimate the average compensation for similar roles.
Employment type
Full Time,
Job posted
Apply before
21 Aug 2026
Experience level
Midweight
Views / Applies
172 / 13

About Canonical Ltd.

Trusted open source for enterprises

Actively Hiring
Verified job posting
This job post has been manually reviewed for authenticity and compliance.

AI Summary

Canonical is hiring an Engineering Manager for MLOps & Analytics to lead a distributed team of engineers. The role combines technical expertise in Python and MLOps tools like Kubeflow and MLFlow with people management responsibilities. The manager will develop team members, conduct code reviews, and collaborate with product managers to define the engineering roadmap. Travel for internal and external events 2-4 times per year is required. The position is fully remote globally.

Role DNA

Job Complexity
Easy Hard
Pace & Pressure
Relaxed Fast-paced
Autonomy Level
Guided Full Ownership
Communication Load
Independent Highly Collaborative
AI Insight The role requires a strong technical background in MLOps and software delivery, along with proven people management skills in a distributed setting, making it challenging but achievable for experienced engineers.

Salary Analysis

Median Market Rate
$170,000
US Market
$140k – 220k
0 $242k
AI Insight No salary was provided in the listing. Based on market data for similar Engineering Manager roles in MLOps, the estimated median salary is $170,000 per year, which is competitive for a remote role at a global open-source company.

Dear Hiring Manager,

I am excited to apply for the Engineering Manager - MLOps & Analytics position at Canonical. With a strong background in software delivery and deep expertise in MLOps tools like Kubeflow and MLFlow, I am confident in leading a distributed team to drive innovative solutions. My experience in open-source contributions and cloud technologies aligns perfectly with Canonical's mission. I look forward to the opportunity to mentor engineers and contribute to the roadmap. Thank you for considering my application.

Can you describe your experience managing a distributed team of engineers? How do you ensure productivity and team cohesion?
I have managed distributed teams for 5 years, using asynchronous communication tools like Slack and regular video stand-ups. I prioritize clear documentation, one-on-one meetings, and team retrospectives to maintain alignment and morale.
What is your approach to implementing MLOps pipelines at scale? Give an example of a project you led.
I led the migration of a legacy ML workflow to a scalable MLOps pipeline using Kubeflow and Feast. We automated model training, versioning, and deployment, reducing time-to-production by 40%.
How do you balance technical contributions with management responsibilities?
I allocate 30% of my time to coding and code reviews, focusing on architectural guidance and unblocking the team. For management, I schedule dedicated blocks for mentoring, strategy, and process improvement.
Can you discuss a time you had to handle a conflict within your team?
Two team members disagreed on the choice of an MLOps tool. I facilitated a data-driven discussion, comparing trade-offs, and we decided to run a proof-of-concept. This resolved the conflict and led to a consensus.
What do you think is the most important skill for an Engineering Manager in the MLOps space?
The ability to bridge the gap between data science and engineering. Understanding both the modeling lifecycle and production infrastructure ensures that pipelines are robust, scalable, and maintainable.

The role of an Engineering Manager at Canonical

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.

 

#LI-remote 

Apply now >

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.

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