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  • Posted: Apr 4, 2024
    Deadline: Not specified
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    We deliver open source to the world faster, more securely and more cost effectively than any other company. If you're interested in a career at Canonical, we are a remote-first company so please apply to any suitable role as skills are valued more than location, despite some having a preferred geographic preference.
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    AI/ML and MLOps Field Engineer

    • 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

    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
    • Demonstrated personal interest in continuous learning and development
    • Practical knowledge of Linux, virtualisation, containers and networking
    • Business-minded technology thinker and problem solver
    • Knowledge of cloud computing concepts & leaders, such as Kubernetes, AWS, Azure, GCP
    • Interest in large-scale enterprise open source - private clouds, machine learning and AI, data and analytics
    • Intermediate level Python programming skills
    • Passion for technology evidenced by personal projects and initiatives
    • The work ethic and confidence to shine alongside motivated colleagues
    • Professional written and spoken English with excellent presentation skills
    • Experience with Linux (Debian or Ubuntu preferred)
    • Excellent interpersonal skills, curiosity, flexibility, and accountability
    • A dynamic person who loves to jump in new projects and interact with people
    • Appreciative of diversity, polite and effective in a multi-cultural, multi-national organisation
    • Thoughtfulness and self-motivation
    • Result-oriented, with a personal drive to follow up and meet commitments
    • Ability to travel internationally, for company events up to two weeks long, and customer or industry meetings

    What you'll learn

    • Architect and deploy AI/ML infrastructures, data processing pipelines and multi-cluster distributed training
    • Wide range of open source applications and skills
    • Work directly with customers in a range of different businesses
    • Real-life and hands-on exposure to a wide range of emerging technologies and tools

    Method of Application

    Interested and qualified? Go to Canonical on boards.greenhouse.io to apply

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