Job
Description
frameworksThe Opportunity: (Brief Overview of the Role) 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 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 What you will need to succeed in the role: (Minimum Qualification and Skills Required) Bachelor's 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. Strong proficiency in Python programming and familiarity with machine learning frameworks such as TensorFlow or Pytorch. Proficiency in implementing and managing security, identity, and access management solutions, leveraging Active Directory, Security Center, and other related tools. Hands-on experience with scripting and automation using tools such as Azure Resource Manager templates, PowerShell, Ansible, or other relevant technologies. Strong understanding of networking concepts and experience in configuring and troubleshooting Azure/AWS Virtual Networks, VPN gateways, and ExpressRoute. Familiarity with cloud-native monitoring, logging, and alerting tools such as Monitor, Log Analytics, Application Insights, and their integration with respective cloud services and applications. Knowledge of best practices in Azure/AWS DevOps, CI/CD pipelines, and experience working in an agile development environment. Excellent troubleshooting skills, with the ability to analyze complex issues in cloud environments and provide scalable solutions. Strong communication and collaboration skills, with the ability to work effectively in a team- oriented, fast-paced environment.
