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

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Job Overview

The Python and Kubernetes Software Engineer - Data, AI/ML & Analytics at Canonical will play a pivotal role in developing and optimizing solutions around data, artificial intelligence, and machine learning. The successful candidate will collaborate closely with cross-functional teams to design, implement, and deploy scalable applications using Python and Kubernetes technologies. They will be responsible for leveraging data-driven insights to build innovative analytics solutions while ensuring best practices in software development and deployment are maintained across projects.

Job Responsibilities

• Develop and maintain robust Python applications tailored for data processing and AI/ML tasks.
• Design and orchestrate containerized applications using Kubernetes for scalable deployment.
• Collaborate with data scientists to enhance and optimize machine learning models and analytics frameworks.
• Implement and maintain CI/CD pipelines to facilitate smooth deployment and updates of projects.
• Conduct code reviews and uphold high standards in software quality and performance.
• Troubleshoot and resolve application issues, ensuring minimal downtime and high service reliability.
• Participate in architecture discussions and contribute to the overall software design strategy.

Qualifications

• Bachelor's degree in Computer Science, Software Engineering, or a related field.
• Proven experience in Python programming with a strong understanding of data structures and algorithms.
• Hands-on experience with Kubernetes and container orchestration principles.
• Familiarity with machine learning frameworks such as TensorFlow, PyTorch, or scikit-learn.
• Strong background in data analytics, data processing, and data visualization tools.
• Excellent problem-solving skills and ability to work in a fast-paced environment.
• Experience with CI/CD tools such as Jenkins, GitLab CI, or Travis CI is an advantage.

Technologies & Tools

This position will utilize a combination of modern software development tools and technologies, primarily focusing on Python for application development. Kubernetes will be essential for managing containerized applications, while various AI/ML frameworks (e.g., TensorFlow, PyTorch) will be used to facilitate model development. Additionally, proficiency in version control systems like Git, CI/CD practices, and cloud platforms (AWS, Google Cloud, etc.) will be critical for providing scalable solutions.

Ideal Candidates

The ideal candidates will be innovative thinkers, passionate about data science and machine learning, and have a solid background in software engineering principles. They should exhibit a strong collaboration spirit, capable of working with cross-functional teams and communicating complex technical concepts clearly. A proactive attitude toward continuous learning and adapting to emerging technologies will also make them strong contenders for this role. Enthusiasm about contributing to Canonical's success through impactful software solutions will be a significant asset.