Python and Kubernetes Software Engineer - Data, Workflows, AI/ML & Analytics

CanonicalCanonical·Remote(Home based - Worldwide)·Work From Anywhere
Software Development
Excel

WFA Digital Insight

As demand for AI and machine learning specialists surges, Canonical's remote Python and Kubernetes Software Engineer role stands out for its focus on open-source innovation. With the company's commitment to global collaboration and free access to primary work, this role appeals to professionals seeking impactful projects. Candidates should be prepared to showcase their expertise in data analytics, MLOps, and Kubernetes, as well as their ability to thrive in a distributed team environment.

Job Description

About the Role

Canonical, a leading open-source software provider, is seeking a Python and Kubernetes Software Engineer to join its teams building solutions for public cloud and private infrastructure. The role involves collaborating on end-to-end data analytics and MLOps solutions, working with popular machine learning tools like Kubeflow, MLFlow, and DVC.

Responsibilities

  • Collaborate on data analytics and MLOps solutions
  • Work with tools like Apache SuperSet, dbt, Airflow, and Temporal
  • Develop solutions for data governance, visualization, and workflow orchestration

Requirements

  • Strong Python and Kubernetes skills
  • Experience with data, workflows, AI/ML, and analytics solutions

Benefits

  • Opportunity to work on open-source projects with global impact
  • Collaboration with a distributed team across multiple time zones

How to Stand Out

  • Showcase your Python and Kubernetes skills through personal projects or contributions to open-source repositories.
  • Highlight experience with data analytics, MLOps, and machine learning tools like Kubeflow and MLFlow.
  • Prepare to discuss your approach to collaborating in a distributed team environment and managing different time zones.
  • Be ready to provide examples of solving complex data workflow problems and optimizing analytics solutions.
  • Consider including a link to your GitHub profile or a personal project that demonstrates your expertise in AI/ML and data analytics.

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