Remote Engineering Manager - MLOps & Analytics

Canonical; United States; Remote; USD 150,000 - 200,000; Full time

Benefits offered by this job

Learning budget

Annual bonus

Remote-first culture

Travel opportunities

Holiday leave

Employee assistance

Job summary

Canonical is seeking an Engineering Manager to lead a distributed team of ML and analytics engineers. You will code review and guide architecture while removing blockers to deliver high-quality software.

You will mentor engineers, shape technical strategy, and collaborate with product managers and architects. This remote-first role involves occasional travel for internal and external events and requires strong Python and MLOps expertise.

Qualifications

• .Proven professional Python development experience, preferably with open source.
• .Strong understanding of the machine learning space and its challenges.
• .Experience designing and implementing MLOps solutions.
• .Exceptional academic track record; willingness to travel up to 4 times a year for internal events.

Responsibilities

• Manage a distributed team of engineers and its MLOps/Analytics portfolio.
• Organize and lead the team's processes to achieve objectives.
• Conduct one-on-one meetings with team members.
• Identify and measure team health indicators.
• Interact with Canonical community and external partners.
• Review code produced by other engineers.
• Attend conferences to represent Canonical and its MLOps solutions.
• Mentor and grow direct reports to reach professional goals.

Skills

Python

MLOps

Open Source

Distributed teams

Code reviews

Leadership

Cloud platforms

Tools

Docker

Kubernetes

Kubeflow

MLFlow

Feast

AWS

Azure

GCP

Job description

Canonical is seeking an Engineering Manager to lead a distributed team of ML and analytics engineers. You will code review and guide architecture while removing blockers to deliver high-quality software.

You will mentor engineers, shape technical strategy, and collaborate with product managers and architects. This remote-first role involves occasional travel for internal and external events and requires strong Python and MLOps expertise.