As an Engineering Manager at Canonical, you will be responsible for leading a team of engineers while being technically sound in MLOps and analytics. Your main responsibility is to ensure the team operates effectively and develops professionally. You will oversee code development, promote best practices, and facilitate the team's focus on productivity.
Key responsibilities include:
- Managing a distributed team of engineers and their MLOps/Analytics portfolio.
- Organizing and leading team processes to achieve objectives.
- Conducting one-on-one meetings and measuring team health indicators.
- Reviewing code produced by team members and providing architectural leadership.
- Mentoring team members and helping them achieve their professional goals.
- Attending conferences to represent Canonical and its MLOps solutions.
We are looking for candidates with a proven track record in software delivery and professional Python development, preferably within open source. A solid understanding of the machine learning landscape and experience designing and implementing MLOps solutions is also essential. Candidates should be willing to travel up to 4 times a year for internal events.
Additional skills that are optional but beneficial include:
- Hands-on experience with machine learning libraries or tools.
- Experience building machine learning solutions for the cloud.
- Familiarity with container technologies (Docker, LXD, Kubernetes).
- Experience with public clouds (AWS, Azure, Google Cloud).
- Interest in software quality and testing.
- Knowledge of working on distributed teams or contributions to open source projects.
Fluency in English is expected.
Benefits include:
- Competitive compensation with annual reviews and performance-driven bonuses.
- Personal learning and development budget of USD 2,000 per year.
- Paid paternity and maternity leave.
- Employee Assistance Program.
- Opportunities for travel to meet colleagues from different locations.
Canonical promotes a diverse and inclusive work environment, treating all applicants fairly regardless of identity.
Location: Dubai, Dubai, United Arab Emirates (Remote)
Work Conditions: Remote, Full-time; Global travel for 2 to 4 weeks per year for internal and external events.
