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| Job Location | Toronto, Ontario, M5A 3N7 |
| Education | Not Mentioned |
| Salary | Not Mentioned |
| Industry | Not Mentioned |
| Functional Area | Not Mentioned |
| Job Type | Full time |
Role: AI/ML Devops Toronto Role name: Developer Role Description: Roles and Responsibilities: Passionate about deep learning and natural language models AIOps/MLOps mindset enabling services and developing pipelines for managing training models and production models.Collaborate with internal application development teams to leverage AI/ML services to solve business objectivesUnderstand security, risks and mitigations to load data and training models securely into Cloud Programming skills with experience in API and Webhook development using Python, Git Actions and Terraform Write and use Azure RM and Terraform templates Understand Azure security features (data protection, authentication, RBAC, etc) Understanding of Public Key Infrastructure (PKI), handling public key and private key certificates in Azure environment for Paas services and applications Ability to troubleshoot Azure, DNS, Azure connectivity, NSG, routing Proficiency in cloud automation using native Azure CLI Understand concepts related to deploying platform and data analytics via CI/CD pipelineEnsure that all cloud solutions follow internally defined security and compliance controls Develop/Consume APIs, SDKs and Webhook for multi-directional integration of cloud orchestration platform with enterprise systems, DevOps Tools and cloud platforms Ability to participate in fast-paced DevOps Engineering teams within Scrum agile processes A critical thinker with strong research and analytics skills Self-motivated with a positive attitude and an ability to work independently and in a teamRequired Skills: 2+ years AI and ML platform engineer 2+ years of experience developing platform orchestration code in Azure Python SDK, Terraform and GitHub Runners Strong expertise with delivering Cloud Infrastructure As Code (IAC) leveraging CI/CD pipelines, Terraform and Git Actions. Demonstrated knowledge of cloud provisioning and administration, cloud bursting, cloud interoperability, cloud disaster recovery and business continuity strategies, as well as performance measurement and monitoring in the cloud Must be a self-starter, demonstrated ability to take independent action to achieve results. Highly developed critical thinking, analytical and problem solving skills Competencies: Digital : Azure Machine Learning (ML) Experience (Years): 6-8