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 be a vital contributor to our innovative projects, focusing on designing and implementing solutions that leverage data science and machine learning. The role involves collaborating with cross-functional teams to build scalable applications, manage data workflows, and enhance analytics capabilities using cutting-edge technologies. This position offers the opportunity to work on impactful projects while promoting best practices in software engineering, data management, and the deployment of models in Kubernetes environments.

Job Responsibilities

• Develop and maintain robust Python applications that efficiently handle data ingestion, processing, and analysis.
• Design and implement scalable AI/ML models and algorithms to extract insights from data.
• Collaborate with data scientists and engineers to integrate machine learning models into production environments using Kubernetes.
• Enhance the data pipeline by incorporating best practices for performance, reliability, and security.
• Participate in code reviews, debugging, and testing processes to ensure software quality.
• Stay updated with the latest advancements in AI/ML technologies and incorporate relevant tools into current projects.
• Contribute to documentation and training materials to facilitate knowledge sharing among team members.

Qualifications

• Bachelor's or Master's degree in Computer Science, Engineering, Data Science, or a related field.
• Proven experience in software development using Python, particularly in data manipulation and machine learning frameworks.
• Strong familiarity with Kubernetes and cloud environments (such as AWS, Google Cloud, or Azure).
• Experience with data science libraries such as NumPy, Pandas, TensorFlow, or PyTorch.
• Knowledge of containerization technologies, CI/CD methodologies, and DevOps practices.
• Excellent problem-solving skills and ability to work collaboratively in a team-oriented environment.
• Strong communication skills, both verbal and written.

Technologies & Tools

In this position, candidates will utilize a wide range of technologies and tools including Python, Docker for containerization, Kubernetes for orchestration, and various data science libraries such as Pandas, NumPy, TensorFlow, or Scikit-learn. Familiarity with cloud platforms such as AWS or Google Cloud is essential, along with version control systems like Git to manage and document the development process.

Ideal Candidates

Ideal candidates will possess a strong analytical mindset, demonstrating not only technical proficiency but also creative problem-solving skills. They should be passionate about data and technology, with a keen interest in continuous learning and adapting to evolving industry trends. The ability to communicate complex concepts effectively to diverse audiences and collaborate with cross-functional teams will ensure success in this dynamic role. Exceptional attention to detail and a commitment to code quality and best practices will distinguish the most suitable applicants for this position.