
AI Studio Expert
7 days ago
Key Responsibilities:
- 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.
- Develop and maintain continuous integration and continuous deployment pipelines for AI applications.
- Automate deployment processes to streamline workflows and reduce time-to-market.
- 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.
- 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.
- 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.
- Ensure all deployments adhere to security standards and compliance regulations.
- Implement and maintain security protocols for both cloud and on-premises environments.
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: HP Fury Z8, Dell 7960 XCTO, and Nvidia GCX Studio A100.
- 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.
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