Engineering Manager - MLOps & Analytics

About the role

Canonical is looking for an Engineering Manager to lead a distributed team focused on MLOps and analytics. You will combine strong technical expertise with people‑management skills to keep the team productive, unblock challenges, and deliver high‑quality machine‑learning solutions.

Key responsibilities

• Manage a globally remote team of engineers working on MLOps and analytics portfolios.
• Organise and lead team processes, set objectives and track health indicators.
• Conduct one‑on‑one meetings, mentor engineers and support their professional growth.
• Review code, guide architecture and ensure best practices in documentation, quality and performance.
• Collaborate with other engineering managers, product managers and architects to define road‑maps.
• Represent Canonical at conferences and engage with the open‑source MLOps community.
• Travel globally for 2‑4 weeks per year for internal and external events.

Required profile

• Proven track record of delivering software projects.
• Professional Python development experience, preferably with open‑source contributions.
• Deep understanding of the machine‑learning ecosystem, its challenges and opportunities.
• Experience designing and implementing MLOps solutions.
• Strong leadership skills to build and sustain high‑performing teams.

Required skills

• Python
• Kubeflow
• MLFlow
• Feast
• Docker
• Kubernetes
• Linux
• LXD
• AWS
• Azure
• Google Cloud
• MLOps

What we offer

• Fully remote work with occasional global travel.
• Opportunity to influence culture and technical direction.
• Access to a vibrant open‑source community and industry conferences.