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

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Job Overview

As a Python and Kubernetes Software Engineer specializing in Data, AI/ML & Analytics at Canonical, you will play a pivotal role in designing and implementing scalable software solutions that leverage advanced data processing and machine learning capabilities. Your expertise in Python programming and Kubernetes orchestration will be vital in enabling robust analytics frameworks that support the development of innovative AI applications. Moreover, you will collaborate with cross-functional teams to enhance our data-intense software offerings while ensuring performance, reliability, and scalability.

Job Responsibilities

• Design and develop Python applications focused on data handling, analytics, and machine learning.
• Utilize Kubernetes for deployment, scaling, and management of containerized applications.
• Collaborate with data scientists and engineers to integrate machine learning models into our software platforms.
• Implement best practices for data management, quality assurance, and code maintainability.
• Participate in code reviews and provide mentorship to junior engineers.
• Conduct performance and optimization enhancements to existing analytics frameworks.
• Stay abreast of industry trends and emerging technologies related to AI and data analytics.

Qualifications

• Bachelor’s degree in Computer Science, Software Engineering, or a related field.
• Proficient in Python, with strong experience in frameworks such as Flask or Django.
• Solid understanding of Kubernetes, including experience in deploying and managing applications on cluster environments.
• Experience with data analysis libraries such as Pandas, NumPy, or similar.
• Familiarity with machine learning frameworks like TensorFlow or PyTorch is highly desirable.
• Strong problem-solving skills and ability to work effectively in collaborative team settings.
• Experience in Git or other version control systems.

Technologies & Tools

The Python and Kubernetes Software Engineer at Canonical will leverage a variety of technologies and tools including, but not limited to, Kubernetes for container orchestration, Docker for containerization, Python for programming, and various data processing libraries such as Pandas and NumPy. Additionally, familiarity with machine learning libraries like TensorFlow or PyTorch will be an asset, alongside utilitarian tools such as Git for version control and CI/CD pipelines for deployment automation.

Ideal Candidates

The ideal candidate for this position will be a proactive and innovative software engineer who is passionate about data and machine learning technologies. They will possess an analytical mindset, combined with a strong foundation in software development practices and cloud-native technologies. Effective communication skills are crucial, as the role requires collaboration across various teams. A keen interest in ongoing learning and adaptation to new technologies will also be essential for success in this fast-evolving environment.