Canonical is a leading provider of open-source software and operating systems, known for its platform, Ubuntu. Our technology is integral to enterprise initiatives such as public cloud, data science, AI, engineering innovation, and IoT. We serve the world's leading public cloud and silicon providers, as well as notable industry leaders across various sectors. As a pioneer of global distributed collaboration, we have a diverse team of over 1,000 colleagues across 70+ countries, with very few roles based in offices. Teams engage in in-person meetings two to four times yearly in various global locations to align on strategy and execution.
We are seeking an MLOps Field Engineer to assist global companies in integrating AI/ML into their operations utilizing the latest open-source technologies on both public and private cloud infrastructures, including Linux and Kubernetes. The ideal candidate will work closely with enterprise sales leads and will be responsible for addressing real-world customer challenges, customer interactions during the presales cycle, and designing ML architectures for external customers.
This role is particularly suited for candidates with a technical background who possess a strong business mindset and are motivated by commercial success. Responsibilities involve working with technologies like Ubuntu, Kubeflow, MLFlow, Feast, DVC, and other analytics and machine learning tools.
Primary Responsibilities:
- Design private and public cloud solutions that fit customer workload requirements.
- Work hands-on with technologies by deploying, testing, and handing over solutions to support teams.
- Architect cloud infrastructure solutions using Kubernetes, Kubeflow, OpenStack, and Spark.
- Deliver on-premise or public cloud solutions (AWS, Azure, Google Cloud).
- Collect and advise on customer business requirements related to Ubuntu and other open-source applications.
- Conduct presentations and demonstrations of Ubuntu Pro and AI/ML capabilities to clients.
- Collaborate with product teams to provide feedback influencing the roadmap.
- Travel internationally, as required, for events and customer meetings.
Requirements:
- Exceptional academic track record from both high school and university.
- Undergraduate degree in a technical subject or equivalent experience.
- Experience in data engineering, MLOps, or big data solutions deployment.
- Proficiency in relevant programming languages (Python, R, Rust).
- Competence in Linux, virtualization, containers, and networking.
- Good understanding of cloud computing concepts and leading platforms (Kubernetes, AWS, Azure, GCP).
- Intermediate level Python programming skills.
- Professional written and spoken English.
What You'll Learn:
- Architect and deploy AI/ML infrastructures and data processing pipelines.
- Work with diverse businesses and gain hands-on experience with emerging technologies.
What We Offer:
- Competitive compensation with performance-driven bonuses.
- Remote work environment with annual compensation reviews.
- Personal learning and development budget of USD 2,000 per year.
- Annual holiday leave, maternity and paternity leave.
- Opportunities for international travel.
Canonical is an equal opportunity employer. We celebrate diversity and strive to create an inclusive environment for all employees.
