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 will play a pivotal role in developing cutting-edge software solutions that enhance data analytics through artificial intelligence and machine learning. This role entails working closely with cross-functional teams to design and implement robust applications using Python and Kubernetes in cloud environments. The successful candidate will contribute to a variety of challenging projects, driving improvements in data management and analytical capabilities, while maintaining high standards of quality and performance.

Job Responsibilities

• Design, develop, and maintain Python applications for data processing and ML model integration.
• Implement and manage Kubernetes clusters to deploy scalable applications and services.
• Collaborate with data scientists and analysts to understand requirements and translate them into technical solutions.
• Optimize data pipelines for efficiency and performance across various cloud environments.
• Conduct code reviews and provide mentorship to junior developers to foster a culture of best practices.
• Participate in Agile methodologies to ensure timely delivery of software solutions.
• Monitor and troubleshoot application performance and resolve issues expeditiously.

Qualifications

• Bachelor's degree in Computer Science, Engineering, or a related field.
• Proven experience in Python programming and application development.
• Strong knowledge of Kubernetes and container orchestration.
• Experience with machine learning frameworks and libraries such as TensorFlow or PyTorch.
• Familiarity with data processing and analytics tools such as Pandas, NumPy, or Spark.
• Understanding of cloud platforms (e.g., AWS, GCP, Azure) and their services.
• Excellent problem-solving skills and a strong analytical mindset.

Technologies & Tools

The Python and Kubernetes Software Engineer will utilize a variety of technologies and tools essential for developing and managing cloud-native applications. Key tools include Python, various machine learning frameworks (such as TensorFlow and PyTorch), Kubernetes for container orchestration, and cloud services like AWS, Google Cloud, or Microsoft Azure. Additional tools used may include data management platforms, CI/CD pipelines, and version control systems such as Git.

Ideal Candidates

Ideal candidates for this position are characterized by their strong technical expertise coupled with a deep passion for data and analytics. They should demonstrate a proactive approach to learning and adapting to new technologies, excellent communication skills to collaborate effectively with diverse teams, and a curious mindset that drives innovation. Furthermore, candidates who thrive in dynamic environments and possess a commitment to quality and performance will find themselves aligning well with the values of Canonical.