DevOps Engineer
4 weeks ago
Responsibilities :
- Design and implement scalable AI/ML solutions on Azure, focusing on GenAI and Cognitive Services.
- Develop and manage MLOps pipelines for model training, validation, and deployment.
- Automate infrastructure provisioning and configuration using IaC (ARM, Bicep, Terraform).
- Ensure security, compliance, and governance standards are met in all AI/ML solutions.
- Collaborate with cross-functional teams to integrate AI into various applications.
- Troubleshoot and resolve issues related to AI/ML infrastructure and deployments.
- Stay updated with the latest advancements in AI/ML and cloud technologies.
Qualifications :
- 8 - 12 years of professional experience in cloud architecture, DevOps, or infrastructure engineering, with at least 3+ years in AI/ML solution design.
- Strong expertise in Azure AI services : Cognitive Services, Azure ML, Azure OpenAI, Synapse,
Data Lake, Bot Services.
- Hands-on programming in .NET/C# or Python (must-have).
- Experience with MLOps frameworks (Azure ML Pipelines, MLflow, Kubeflow).
- Proficiency in CI/CD, IaC (ARM, Bicep, Terraform), and Kubernetes/AKS.
- Expertise in Windows Server (primary) and Linux/Unix (secondary) environments.
- Familiarity with data engineering pipelines and AI integration patterns.
- Knowledge of Responsible AI, security, compliance, and governance frameworks.
- Bonus : Experience deploying GenAI solutions with Azure OpenAI or integrating third-party AI & Certifications :
- Preferred Certifications :
- Microsoft Certified : Azure Solutions Architect Expert
- Microsoft Certified : Azure AI Engineer Associate
- Microsoft Certified : Azure Data Scientist Associate
- Kubernetes CKA/CKAD, Terraform Associate
(ref:hirist.tech)-
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