About the role
As an Engineering Manager at Canonical, you will run an effective distributed team while remaining technically strong. Your main responsibility is developing the engineers you manage — helping them grow, do meaningful work, find professional satisfaction, and collaborate well with colleagues and the community. You will review code and provide architectural leadership while keeping your team focused, productive, and unblocked. You will work closely with other Engineering Managers, product managers, and architects to produce an engineering roadmap with ambitious and achievable goals. The team's focus is on popular open-source machine learning tools including Kubeflow, MLFlow, and Feast. Day-to-day you will manage the team's MLOps and Analytics portfolio, run one-on-ones, track team health indicators, review code, attend conferences to represent Canonical, and mentor your direct reports. The role involves 2 to 4 weeks of global travel per year for internal and external events.
What we're looking for
Proven track record of professional software delivery. Professional Python development experience, preferably with open-source contributions. Proven understanding of the machine learning space, its challenges and opportunities. Experience designing and implementing MLOps solutions. Exceptional academic track record from high school and preferably university. Willingness to travel up to 4 times a year for internal events. Hands-on experience with machine learning libraries or tools is a plus. Experience with container technologies such as Docker, LXD, or Kubernetes is a plus. Experience with public clouds including AWS, Azure, or Google Cloud is a plus. Experience working on distributed open-source teams is an advantage.