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 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 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 30% of time for internal, external events and customer meetings.

What we are looking for in you

Exceptional academic track record from both high school and university,

Undergraduate degree in a technical subject or a compelling narrative about your alternative chosen path,

Experience in data engineering, MLOps, or big data solutions deployment,

Experience with a relevant programming language, like Python, R, or Rust,

Confidence to respectfully speak up, exchange feedback, and share ideas without hesitation,

Track record of going above-and-beyond expectations to achieve outstanding results,