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, and Analytics at Canonical, you will be responsible for developing scalable AI/ML solutions and analytics tools that leverage our advanced data processing capabilities. Your primary role will involve designing, implementing, and maintaining robust software systems using Python in conjunction with Kubernetes orchestration. You will collaborate with cross-functional teams to enhance data pipelines and analytics functionalities, ensuring high-performance data handling and efficient model training processes.

Job Responsibilities

• Design and implement software solutions using Python, focusing on data processing and AI/ML model development.
• Utilize Kubernetes to orchestrate and manage containerized applications in a scalable manner.
• Develop and optimize data pipelines to support machine learning workflows and analytics.
• Collaborate with data scientists and engineers to integrate AI/ML algorithms into production systems.
• Participate in code reviews, design discussions, and push for best practices in software development.
• Monitor, troubleshoot, and maintain the performance of existing applications and data systems.
• Stay updated on industry trends and emerging technologies related to data science and cloud-native applications.

Qualifications

• Bachelor's degree in Computer Science, Information Technology, or a related field.
• Proficiency in Python programming with a strong focus on software development practices.
• Hands-on experience with Kubernetes and Docker for container orchestration.
• Familiarity with data processing frameworks such as Apache Spark, Kafka, or similar.
• Experience with machine learning frameworks, such as TensorFlow, PyTorch, or scikit-learn.
• Knowledge of cloud services (AWS, GCP, Azure) and CI/CD pipelines.
• Strong analytical and problem-solving skills, with the ability to work collaboratively in a team-oriented environment.

Technologies & Tools

In this position, you will work with a wide range of cutting-edge technologies, including Python for software development, Kubernetes for container orchestration, and various data processing tools like Apache Spark for handling large-scale data. You will also utilize machine learning frameworks such as TensorFlow or PyTorch to build and deploy models effectively. Familiarity with cloud platforms like AWS or GCP will be essential for integrating the software solutions within a cloud-native environment.

Ideal Candidates

The ideal candidates for this position will possess a strong technical acumen alongside effective communication skills. They should be proactive, innovative, and eager to tackle complex challenges in data science and software engineering. Successful applicants will have a collaborative mindset and be comfortable working in a fast-paced environment, demonstrating a commitment to continuous learning and improvement in their expertise within data, AI/ML, and analytics.