Job
Description
We are seeking a talented ML Ops engineer to join our team and play a key role in deploying, managing and optimizing machine learning models in production. The ideal candidate will have a strong background in both machine learning and software engineering, with experience in DevOps practices and cloud computing. Roles Responsibilities: Collaborate with data scientists and software engineers to deploy machine learning models into production environments. Design and implement scalable and reliable ML pipelines for model training, evaluation and deployment. Develop and maintain infrastructure automation scripts for provisioning, configuration, and orchestration using platforms such as Resource Manager (ARM) templates, Automation, PowerShell, or other relevant tools. Optimize ML pipelines for efficiency, scalability and cost-effectiveness Monitor, optimize, and troubleshoot Azure/AWS resources and services to ensure high availability, reliability, and performance of cloud-based applications and systems. Implement security policies, access controls, and encryption protocols to safeguard Azure/AWS environments and data, adhering to compliance and governance requirements. Collaborate with development teams to streamline the continuous integration and continuous deployment (CI/CD) process in Azure/AWS DevOps or similar tools for efficient application delivery. Provide expertise and support in areas such as Azure/AWS cost management, capacity planning, scalability, and disaster recovery strategies. Participate in the evaluation of new Azure/AWS offerings, technologies, and services to drive innovation and improve the overall cloud environment. Qualifications External/Internal What you will need to succeed in the role: (Minimum Qualification and Skills Required) Bachelors degree in Computer Science, Information Technology, or a related field; relevant certifications such as Microsoft Certified: Azure Administrator Associate or Microsoft Certified: Azure Solutions Architect Expert preferred. INTERNAL Strong proficiency in Python programming and familiarity with machine learning frame works such as TensorFlow or Pytorch. Proficiency in implementing and managing security, identity, and access management solutions, leveraging Active Directory, Security Center, and other
