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

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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.

Overview

Canonical is seeking a highly skilled Python and Kubernetes Software Engineer to join our dynamic team, focusing on Data, AI/ML, and Analytics. This role involves developing robust software solutions that leverage cutting-edge technologies to analyze data and implement machine learning models. The engineer will work closely with cross-functional teams to design, build, and maintain applications that enhance data insights and facilitate decision-making processes.

Job Responsibilities

• Develop, test, and deploy data-intensive applications using Python and Kubernetes.
• Collaborate with data scientists to implement AI/ML algorithms and models into production.
• Design and maintain scalable architecture for data ingestion, storage, and processing.
• Ensure system reliability and performance through effective monitoring and troubleshooting.
• Work with cloud platforms to optimize solutions for maximum efficiency and cost-effectiveness.
• Document software designs, processes, and architectures for future use and reference.
• Engage in code reviews and provide constructive feedback to improve software quality.

Qualifications

• Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
• Proficiency in Python programming for application and systems development.
• Significant experience with Kubernetes for container orchestration and deployment.
• Strong understanding of data structures, algorithms, and performance optimization techniques.
• Experience with machine learning frameworks such as TensorFlow, PyTorch, or similar.
• Knowledge of cloud services (AWS, Google Cloud, Azure) and DevOps practices.
• Excellent problem-solving skills and the ability to work independently as well as in a team.

Technologies & Tools

The Software Engineer position at Canonical will primarily utilize various technologies and tools, including Python for application development, Kubernetes for container orchestration, and a range of cloud platforms for deploying AI and Machine Learning solutions. Familiarity with Docker, Git, and software development methodologies is also essential to ensure the efficient delivery of software solutions.

Ideal Candidates

The ideal candidates for this position are proactive individuals who are passionate about leveraging technology for innovative data solutions. They should possess strong analytical skills with the capability to adapt to new challenges and emerging technologies. A collaborative spirit and excellent communication skills are vital to work effectively with diverse teams. Moreover, candidates should demonstrate a commitment to continuous learning and improvement in the rapidly evolving fields of data science and machine learning.