Remote opportunity at
CanonicalEngineering Manager - MLOps & Analytics
This is a full-time, globally remote Engineering Manager role leading a distributed team that works on Canonical's MLOps and analytics portfolio. The team builds machine learning…
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About This Role
This is a full-time, globally remote Engineering Manager role leading a distributed team that works on Canonical's MLOps and analytics portfolio. The team builds machine learning operations solutions around open source tools such as Kubeflow, MLFlow and Feast. The manager needs strong technical skills, yet the core job is running a productive team and help its members grow as engineers. The role involves organising team processes to meet objectives, holding…
Job Description
This is a full-time, globally remote Engineering Manager role leading a distributed team that works on Canonical's MLOps and analytics portfolio. The team builds machine learning operations solutions around open source tools such as Kubeflow, MLFlow and Feast.
The manager needs strong technical skills, yet the core job is running a productive team and help its members grow as engineers. The role involves organising team processes to meet objectives, holding one-to-one meetings, measuring team health, mentoring direct reports toward their professional goals, and reviewing code written by other engineers. The manager also drafts the engineering roadmap with peer managers, product people and architects, and champions sound practice in documentation, quality and performance. Work includes engaging with the open source community and speaking for Canonical and its MLOps offerings at industry conferences. Trips total 2 to 4 weeks annually across internal and external events.
Applicants should have a demonstrated history of shipping software professionally, plus Python development experience, ideally in open source. They need Demonstrated grasp of machine learning, including its difficulties, and a track record building MLOps solutions from design to rollout. An exceptional academic record and a willingness to travel up to four trips a year for internal gatherings are also expected. Useful extras include hands-on work with machine learning libraries, building automated ML solutions for the cloud, container technologies, public cloud platforms, and open source contributions. Canonical describes itself as founder-led and profitable.
Responsibilities
- Oversee a spread-out group of engineers and the MLOps and analytics portfolio
- Organise and lead the team's processes to achieve its objectives
- Hold one-to-one meetings with team members
- Track indicators of team health and act on them
- Engage with the open source community
- Read and critique code written by teammates
- Speak for Canonical and its MLOps offerings at industry conferences
- Mentor direct reports and help them reach their professional goals
Requirements
- Proven professional experience of software delivery
- Professional Python development experience, ideally in open source
- Demonstrated grasp of machine learning, including its difficulties
- Track record building MLOps solutions from design to rollout
- Willingness to travel up to four trips a year for internal gatherings
Qualifications
- Strong academic record from high school and preferably university
- Practical use of ML libraries or tooling
- History of creating heavily automated ML solutions for cloud platforms
- Experience with container technologies such as Docker, LXD and Kubernetes
- Experience with public clouds such as AWS, Azure and Google Cloud
- Demonstrated open source contributions
Core Skills
Benefits
- Annual compensation review and a bonus tied to performance
- USD 2,000 each year for personal learning and development
- Twice-yearly in-person team sprints in a distributed setup
- Annual holiday leave, plus maternity and paternity leave
- Employee Assistance Programme
- Priority Pass access, plus upgraded seats on long-haul trips to company events
Frequently Asked Questions
Answers are based only on the employer’s listing; where it doesn’t say, neither do we.
Is this MLOps Engineering Manager role remote?
Yes. The posting describes it as a globally remote role.
What experience is required?
The posting asks for professional Python development experience, a proven understanding of machine learning, and a track record building MLOps solutions from design to rollout.
How much travel is expected?
The role involves 2 to 4 weeks of travel per year for events, and a willingness to travel up to four trips a year for internal gatherings.
Is the role full-time, and what is the salary?
The role is full-time, and the posting does not specify a base salary. It mentions a bonus tied to performance.
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