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CanonicalAI & Machine Learning 17d ago

MLOps Field Engineer

Remote (Global)
Full-time
Not Mentioned
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Job Description

Canonical is the company behind Ubuntu, the platform powering the world's public clouds and AI initiatives. They are hiring an MLOps Field Engineer to help global enterprises embrace AI/ML using open-source capabilities on public and private clouds. This is not a pure software development role. It is for Solutions Architects and Engineers who enjoy customer conversations, designing architectures, and solving complex problems like training LLMs on hybrid clouds or processing millions of events in real-time.

Key Responsibilities

  • Architecture Design: Architect cloud infrastructure solutions using Kubernetes, Kubeflow, OpenStack, and Spark to fit customer workload needs.
  • Implementation: Work hands-on to deploy, test, and hand over solutions to support teams. You will use Python to develop Kubernetes operators and Infrastructure-as-Code.
  • Consulting: Collect business requirements and advise customers on Ubuntu and open-source applications (Feast, DVC, MLFlow).
  • Tech Stack Management: Work across the entire Linux stack, from kernel and networking to storage and applications.
  • Global Collaboration: Travel up to 30% of the time for internal sprints (in interesting locations) and customer meetings.

Requirements

  • Academic Excellence: Canonical is unique in requiring an exceptional academic track record from both high school and university.
  • Technical Background: Undergraduate degree in a technical subject or a compelling narrative about your path.
  • Experience: Experience in Data Engineering, MLOps, or Big Data deployment.
  • Programming: Intermediate level Python skills, or experience with R/Rust.
  • Cloud & Linux: Practical knowledge of Linux (Debian/Ubuntu), Virtualization, Containers, and Kubernetes.
  • Communication: Professional written and spoken English with excellent presentation skills.

Benefits

  • Remote First: Fully distributed work environment.
  • Team Sprints: Twice-yearly team sprints in person at international locations.
  • Learning: Personal learning budget of $2,000 USD per year.
  • Travel Perks: Priority Pass and upgrades for long-haul events.

Safety First

  • Never pay for a job application.
  • Do not share sensitive bank info.
  • Verify the client before starting work.