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 crucial role in driving the development and implementation of solutions leveraging data-driven insights and machine learning capabilities. This role involves collaborating with cross-functional teams to design, develop, and enhance applications using Python and Kubernetes in order to harness the full potential of data analytics and artificial intelligence. The successful candidate will be adept at tackling complex challenges in software engineering and be committed to optimizing processes and improving overall system performance.

Job Responsibilities

• Design, develop, and maintain robust applications in Python, ensuring high performance and responsiveness.
• Implement and manage container orchestration using Kubernetes, optimizing deployment and scaling of applications.
• Collaborate with data scientists and analysts to understand business needs and translate them into technical requirements.
• Conduct code reviews, maintain coding standards, and ensure the quality of deliverables.
• Optimize and streamline data pipelines, ensuring efficient data flow for AI/ML models.
• Participate in agile development processes, contributing to sprint planning and retrospectives.
• Troubleshoot and debug applications, providing technical support and solutions to issues as they arise.
• Stay updated with emerging technologies and industry trends related to data analytics and software engineering.

Qualifications

• Bachelor’s degree in Computer Science, Engineering, or a related field; advanced degrees are a plus.
• Strong proficiency in Python programming, with experience in frameworks such as Django or Flask.
• Hands-on experience with Kubernetes for container orchestration, including configuration and monitoring.
• Familiarity with data analysis and machine learning libraries (e.g., Pandas, NumPy, Scikit-learn).
• Solid understanding of APIs and microservices architecture.
• Experience with continuous integration and deployment (CI/CD) practices.
• Proven track record of working in an agile development environment.
• Excellent problem-solving skills and attention to detail.

Technologies & Tools

This position primarily utilizes Python programming language for application development, Kubernetes for container management and orchestration, and various data processing libraries such as Pandas and NumPy for analytics and machine learning tasks. Familiarity with CI/CD tools (e.g., Jenkins, Travis CI) and cloud platforms (AWS, Azure, GCP) is also essential to streamline deployment processes and enhance collaborative efforts with the data science team.

Ideal Candidates

The ideal candidates for this role possess a strong technical acumen paired with excellent interpersonal skills, allowing for effective collaboration within teams. They should demonstrate a proactive approach to learning and adapting to new tools and technologies while being committed to delivering high-quality results. A strong analytical mindset, organizational skills, and an ability to tackle complex problems with innovative solutions make for a successful Python and Kubernetes Software Engineer in the Data, AI/ML & Analytics domain at Canonical.