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

This job was posted over 30 days ago, so it has most likely closed. See newer jobs like it.

Written by AI from the job title and company, not by Canonical, so some details may not match this job. The employer's own page has the real description.

Job Overview

The Python and Kubernetes Software Engineer - Data, AI/ML & Analytics at Canonical plays a critical role in designing, developing, and deploying innovative solutions in the realm of data analytics, artificial intelligence, and machine learning. In this position, you will work collaboratively with cross-functional teams to enhance data-driven decision-making through cutting-edge technology. Your expertise in Python and Kubernetes will be instrumental in orchestrating solutions that optimize the use of data and facilitate the delivery of AI/ML models in production environments.

Job Responsibilities

• Design, develop, and maintain scalable data pipelines and AI/ML workflows using Python.
• Deploy and manage containerized applications using Kubernetes in cloud environments.
• Collaborate with data scientists and analysts to understand requirements and build data-driven solutions.
• Monitor system performance and troubleshoot issues related to data processing and model deployment.
• Ensure best practices in software development, including testing, version control, and documentation.
• Participate in Agile development processes and contribute to continuous integration/continuous deployment (CI/CD) practices.
• Stay abreast of industry trends in data, AI/ML, and analytics to inform best practices and technology choices.

Qualifications

• Bachelor's degree in Computer Science, Engineering, or a related field.
• Proven experience in software development, particularly with Python in data environments.
• Strong understanding of Kubernetes and container orchestration.
• Experience with data analytics and machine learning frameworks (e.g., TensorFlow, PyTorch, Scikit-learn).
• Familiarity with cloud platforms such as AWS, Azure, or Google Cloud.
• Knowledge of databases, both SQL and NoSQL, and data storage solutions.
• Excellent problem-solving skills and ability to work under pressure in a fast-paced environment.

Technologies & Tools

This position will utilize a variety of technologies and tools including Python for programming and scripting, Kubernetes for application deployment and management, TensorFlow or PyTorch for machine learning model development, and various databases (e.g., PostgreSQL, MongoDB) for data storage. Familiarity with CI/CD tools such as Jenkins or GitLab, as well as cloud services from providers like AWS or Google Cloud, will also be essential in this role.

Ideal Candidates

The ideal candidate for this position will be an innovative thinker with a passion for leveraging technology to solve complex data challenges. They will possess strong analytical skills and a detail-oriented mindset, allowing them to effectively analyze data and improve processes. A collaborative temperament and excellent communication skills are crucial, as they will regularly interface with teams across the company. A proactive attitude towards learning new technologies and keeping up-to-date with industry trends will further distinguish a successful candidate in this dynamic role.