Azure AI Studio Expert
4 weeks ago
Urgent requirement for Azure AI Studio for Bangalore Location.
Experience : 8-14 Yrs
Job Location : Bangalore
Job Description :
Key Responsibilities :
Cloud Infrastructure Management :
- Design, deploy, and manage AI solutions on Azure AI Studio and Google Cloud Platform (GCP).
- Optimize cloud resources to ensure cost-effectiveness and high performance.
CI/CD Pipeline Development :
- Develop and maintain continuous integration and continuous deployment pipelines for AI applications.
- Automate deployment processes to streamline workflows and reduce time-to-market.
Hardware Integration :
- Manage and configure specialized hardware workstations including HP Fury Z8, Dell 7960 XCTO, and Nvidia GCX Studio A100.
- Ensure seamless integration between cloud services and on-premises hardware resources.
AI/ML Operations :
- Implement AI Ops, ML Ops, and RAG Ops practices to enhance the reliability and scalability of AI systems.
- Monitor system performance, troubleshoot issues, and implement improvements.
Collaboration and Support :
- Collaborate with cross-functional teams to understand requirements and deliver robust AI solutions.
- Provide technical support and guidance to team members regarding DevOps best practices and tools.
Security and Compliance :
- Ensure all deployments adhere to security standards and compliance regulations.
- Implement and maintain security protocols for both cloud and on-premises environments.
Qualifications :
Education :
Bachelor's degree in Computer Science, Engineering, or a related field. Master's degree preferred.
Experience :
- Proven experience as a DevOps Engineer, preferably within AI or machine learning environments.
- Strong expertise in Azure AI Studio and developing AI solutions on the Azure platform.
- Experience with Google Cloud Platform (GCP) in deploying and managing AI solutions.
Technical Skills :
- Proficiency with cloud services, including compute, storage, networking, and AI/ML tools on Azure and GCP.
- Hands-on experience with CI/CD tools such as Jenkins, GitLab CI, or Azure DevOps.
- Familiarity with containerization and orchestration technologies like Docker and Kubernetes.
- Knowledge of infrastructure as code (IaC) tools such as Terraform or Azure Resource Manager.
Experience with specialised hardware workstations :
1. HP Fury Z8
2. Dell 7960 XCTO
3. Nvidia GCX Studio A100
4. Understanding of AI Ops, ML Ops, and RAG Ops methodologies.
Soft Skills :
- Strong problem-solving skills and attention to detail.
- Excellent communication and teamwork abilities.
- Ability to manage multiple tasks and prioritize effectively in a fast-paced environment.
Preferred Qualifications :
- Certifications in Azure (e.g., Azure DevOps Engineer Expert) or Google Cloud (e.g., Professional DevOps Engineer).
- Experience with monitoring and logging tools such as Prometheus, Grafana, or Azure Monitor.
- Knowledge of scripting languages like Python, Bash, or PowerShell.
- Familiarity with version control systems, particularly Git.
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