Azure ML DevOps Engineer

• Contribute significantly to the creation and upkeep of the pipelines and infrastructure needed for the end-to-end deployment and administration of machine learning models on the Azure platform
• Enable the seamless integration of ML models into production systems and the effective management of ML workloads by engaging with data scientists, ML engineers, and software developers
• Ensure that the architecture and pipelines for end-to-end ML model deployment on the Azure platform are designed, developed, and maintained
• Utilizing the Azure Machine Learning service or Azure ML Ops, work with data scientists and ML engineers to bundle, containerize, and deploy ML models
• Create and maintain automated CI/CD pipelines for the development, testing, and deployment of ML models
• Create and maintain automated data pipelines for effective feature engineering, data intake, and preprocessing
• Implement model management and version control systems to monitor and regulate changes to ML models throughout their lifecycles
• Set up and optimize computing infrastructures and resources for scalable and effective ML model inference
• Incorporate ML models into production systems and make sure their scalable and reliable deployment by working with software engineers
• Identify and fix performance problems, monitor and troubleshoot ML models and infrastructure, and maximize resource use
• Keep abreast of the most recent Azure ML technologies, services, and best practices and proactively suggest and implement changes

Job Requirements:

• Bachelor s/Master s degree in Engineering, Computer Science (or equivalent experience)
• At least 6+ years of relevant experience as an Azure ML DevOps Engineer
• 6-8+ years of experience as a DevOps Engineer, ML Engineer, or in a related position
• Experience with the Azure Machine Learning service, Azure ML Ops, and other Azure ML services in tremendous detail
• Demonstrable experience managing cloud infrastructure using Azure and Databricks
• Familiarity with scripting and programming in languages like Python, PowerShell, or Bash
• Extensive knowledge of CI/CD tools like GitLab CI/CD, Jenkins, or Azure DevOps
• Comprehensive understanding of infrastructure as code, automation, and other DevOps concepts
• Prior knowledge of orchestration tools like Kubernetes and container technologies like Docker
• Strong familiarity with the principles and applications of cloud computing, including Microsoft Azure
• Thorough understanding of ML model management and deployment procedures
• Strong ability to solve problems and troubleshoot
• Demonstrable experience working on projects through remote work is required
• A knack to recognize problems and efficiently fix them
• Excellent interpersonal and teamwork abilities are required to work well with cross-functional teams
• Nice to have some Azure certifications related to ML or DevOps
• Great English communication skills, both spoken and written