Engineering Manager - MLOps & Analytics
Job Summary
Job Description
Canonical is seeking an Engineering Manager - MLOps & Analytics to lead a distributed team building scalable machine learning and analytics solutions using open-source technologies. This role combines technical leadership with team management to deliver high-quality MLOps systems and drive innovation in machine learning infrastructure.
Responsibilities:
- Lead and manage a distributed team of engineers focused on MLOps and analytics
- Define and implement engineering processes to ensure productivity and quality
- Review code and provide architectural guidance for machine learning systems
- Collaborate with product managers and architects to define roadmaps and deliver solutions
- Mentor team members and support their professional growth
- Engage with the open-source community and represent Canonical at events
Requirements:
- Strong experience in Python development and software delivery
- Proven experience designing and implementing MLOps solutions
- Understanding of machine learning tools such as Kubeflow, MLflow, or Feast
- Experience with cloud platforms and container technologies (Docker, Kubernetes)
- Strong leadership and team management experience
- Excellent communication and collaboration skills
Benefits:
- Remote-first work environment with global collaboration
- Annual learning and development budget
- Performance-based bonuses and compensation reviews
- Paid leave and parental benefits
- Opportunities for travel and participation in global events
Canonical offers an innovative and collaborative environment where leaders drive the development of open-source machine learning solutions while building high-performing engineering teams.
