Canonical

The role of an Engineering Manager at Canonical As an Engineering Manager at Canonical, you must be technically strong, but your main responsibility is to run an effective team and develop the colleagues you manage. You will develop and review code as a leader, while at the same time staying aware of that the best way to improve the product is to ensure that the whole team is focused, productive and unblocked. You are expected to help them grow as engineers, do meaningful work, do it outstandingly well, find professional and personal satisfaction, and work well with colleagues and the community. You will also be expected to be a positive influence on culture, facilitate technical delivery, and regularly reflect with your team on strategy and execution. You will collaborate closely with other Engineering Managers, product managers, and architects, producing an engineering roadmap with ambitious and achievable goals. We expect Engineering Managers to be fluent in the programming language, architecture, and components that their team uses, in this case popular open-source machine learning tools like Kubeflow, MLFlow, and Feast. Code reviews and architectural leadership are part of the job. The commitment to healthy engineering practices, documentation, quality and performance optimisation is as important, as is the requirement for fair and clear management, and the obligation to ensure a high-performing team. Location: This is a Globally remote role. What your day will look like - Manage a distributed team of engineers and its MLOps/Analytics portfolio - Organize and lead the team’s processes in order to help it achieve its objectives - Conduct one-on-one meetings with team members - Identify and measure team health indicators - Interact with a vibrant community - Review code produced by other engineers - Attend conferences to represent Canonical and its MLOps solutions - Mentor and grow your direct reports, helping them achieve their professional goals - Work from home with global travel for 2 to 4 weeks per year for internal and external events What we are looking for in you - A proven track record of professional experience of software delivery - Professional python development experience, preferably with a track record in open source - A proven understanding of the machine learning space, its challenges and opportunities to improve - Experience designing and implementing MLOps solutions - An exceptional academic track record from both high school and preferably university - Willingness to travel up to 4 times a year for internal events Additional skills that you might also bring The following skills may be helpful to you in the role, but we don't expect everyone to bring all of them. - Hands-on experience with machine learning libraries, or tools. - Proven track record of building highly automated machine learning solutions for the cloud. - Experience with building machine learning models - Experience with container technologies (Docker, LXD, Kubernetes, etc.) - Experience with public clouds (AWS, Azure, Google Cloud) - Experience in the Linux and open-source software world - Working knowledg

Canonical is a leading provider of open source software and operating systems to the global enterprise and technology markets. Our platform, Ubuntu, is very widely used in breakthrough enterprise initiatives such as public cloud, data science, AI, engineering innovation, and IoT. Our customers include the world's leading public cloud and silicon providers, and industry leaders in many sectors. The company is a pioneer of global distributed collaboration, with 1200+ colleagues in 75+ countries and very few office-based roles. Teams meet two to four times yearly in person, in interesting locations around the world, to align on strategy and execution. The company is founder-led, profitable, and growing. We are hiring an MLOps Field Engineer to help global companies embrace AI/ML in their business, using the latest open source capabilities on public and private cloud infrastructure, Linux and Kubernetes. Our team applies expert insights to real-world customer problems, enabling the enterprise adoption of Ubuntu, Kubeflow, MLFlow, Feast, DVC and related analytics, machine learning and data technologies. We are working to create the world's best open source data platform, covering traditional SQL databases and today's NoSQL data stores, as well as the machinery which turns data into insights and executable models. The people who love this role are MLOps engineers who enjoy customer conversations and solving customer problems during the presales cycle. They are solutions architects who like to solve customer problems through architecture, presentations and training. This role is highly focused on designing ML architectures for external customers. It is not a software development role. This role is particularly suited to candidates with a technical background who are business minded and driven by commercial success. This role is on our global Field Engineering team and will work closely with enterprise sales leads. We are specifically looking for people interested in solving the most difficult problems in modern data architectures. Training LLMs on multiple Kubernetes clusters deployed on a hybrid cloud infrastructure with GPU sharing across multiple teams? Processing 10M events in real time for financial transactions? Object detection on 10k parallel 4K video streams? These are the problems we solve day to day. Location : Most of our colleagues work from home. We are growing teams in EMEA, Americas and APAC time zones, so can accommodate candidates from almost any country. What your day will look like The global Field Engineering team members are Linux and cloud solutions architects for our customers, designing private and public cloud solutions fitting their workload needs. They are the cloud consultants who work hands-on with the technologies by deploying, testing and handing over the solution to our support or managed services team at the end of a project. They are also software engineers who use Python to develop Kubernetes operators and Linux open source infrastructure-as-code. - Work across the entire Linux stack, from kernel, networking, storage, to applications, - Architect cloud infrastructure solutions like Kubernetes, Kubeflow, OpenStack and Spark, - Deliver solutions either on-premise or in public cloud (AWS, Azure, Google Cloud), - Collect customer business requirements and advise them on Ubuntu and relevant open source applications, - Grow a healthy, collaborative engineering culture in line with the company values, - Deliver presentations and demonstrations of Ubuntu Pro and AI/ML capabilities to prospective and current clients, - Liaise with