Job ID: JOB_ID_11144
Job Summary
We are seeking an experienced Azure Administrator with strong AI/ML platform exposure to manage, optimize, and support cloud infrastructure and machine learning environments on Microsoft Azure. The ideal candidate will have hands-on experience with Azure Machine Learning, MLOps, and cloud infrastructure management, ensuring scalable, secure, and high-performing AI solutions.
Key Responsibilities
Azure Infrastructure Administration
- Manage and administer Azure cloud environments including VMs, storage, networking, and security
- Deploy, monitor, and maintain Azure resources ensuring high availability and performance
- Implement cost optimization, governance, and resource tagging strategies
- Configure and manage Azure Active Directory (AAD), RBAC, and policies
AI/ML Platform Management
- Support and manage Azure Machine Learning (AML) workspaces, compute instances, and pipelines
- Enable model deployment, monitoring, and lifecycle management (MLOps)
- Work with Azure AI services, Cognitive Services, and OpenAI integrations
- Manage ML compute resources and environments for training and inference workloads
- Implement monitoring, logging, and alerting for ML workloads
- Azure provides dedicated roles like AI Administrator with full control over ML and AI services, including compute, storage, and monitoring integrations
DevOps & Automation
- Implement CI/CD pipelines for ML models and infrastructure (Azure DevOps/GitHub Actions)
- Automate deployments using ARM templates, Bicep, or Terraform
- Manage containerized workloads using Docker & Kubernetes (AKS)
Security & Compliance
- Ensure cloud security best practices, including identity management and network security
- Implement data protection, encryption, and compliance policies
- Perform vulnerability assessments and remediate risks
Monitoring & Performance Optimization
- Use Azure Monitor, Log Analytics, and Application Insights
- Monitor system health, troubleshoot issues, and optimize performance
- Ensure SLA adherence and uptime for production systems
Collaboration
- Work closely with Data Scientists, ML Engineers, and DevOps teams
- Support model deployment, experimentation, and production scaling
- Participate in architecture discussions and solution design
Required Skills
Azure Core
- Azure VMs, Networking (VNet, NSG, Load Balancer), Storage
- Azure Active Directory (AAD), RBAC
- Azure Monitor, Log Analytics
AI/ML & Data
- Azure Machine Learning (AML)
- MLOps concepts (model deployment, monitoring, retraining)
- Experience with Python, ML frameworks (TensorFlow/PyTorch basic understanding)
DevOps & Automation
- Azure DevOps / GitHub Actions
- Infrastructure as Code (Terraform / ARM / Bicep)
- Containers (Docker, Kubernetes/AKS)
Preferred Qualifications
- Azure Certifications (AZ-104, AZ-400, AI-102, DP-100)
- Experience with Azure OpenAI / Cognitive Services
- Knowledge of data platforms (Azure Data Factory, Synapse, Databricks)
- Experience with event-driven architectures and microservices
Soft Skills
- Strong problem-solving and troubleshooting ability
- Excellent communication and collaboration skills
- Ability to work in fast-paced, production environments
Nice to Have
- Experience with GenAI / LLM deployment on Azure
- Exposure to GPU-based ML workloads
- Knowledge of data governance and model explainability
Special Requirements
Only local candidate who can take F2F Interview.
Compensation & Location
Salary: $100,000 – $150,000 per year
Location: Burlington, MA
Recruiter / Company – Contact Information
Recruiter / Employer: Valzo Soft Solutions
Email: manish@valzosoft.com
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