AIML and MLOps Field Engineer

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 1000+ colleagues in 70+ countries and very few roles based in offices. 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 AI/ML and MLOps Field Engineer to help global companies embrace AI 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 software engineers who enjoy customer conversations and solving customer problems during the presales cycle. They are are developers who like to solve customer problems through architecture, presentations and training. Ubuntu is used by pretty much every enterprise in the world, in every industry. This is a fantastic opportunity to learn about the open source technology landscape and develop your business technology insights. You will see first hand in various industries how Linux - and Ubuntu in particular - is shaping innovation and changing the world for the better. 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 K8s 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 product teams to give them feedback on requirements to influence roadmap Work collaboratively with your sales team to reach our common targets Global travel up to 25% of time for internal and external events and 25% to customer meetings