
Azure DevOps Engineer
3 weeks ago
Job Title : Senior DevOps Engineer - AI/ML
Experience : 4- 7years
Relevant Experience : 5 years
Location : Bengaluru
Mode : 6 month + ext.
Job Summary :
We are seeking an experienced Senior DevOps Engineer to support the deployment, monitoring, and scaling of AI/ML models and infrastructure. The successful candidate will bridge the gap between data science and operations, ensuring that AI solutions are robust, scalable, and production-ready. This role requires a strong foundation in DevOps tools, containerization, and cloud platforms, as well as experience with MLOps tools and scripting languages.
Key Responsibilities :
- AI/ML Model Deployment : Deploy AI/ML models in production environments, ensuring scalability, reliability, and performance.
- Infrastructure Management : Manage and maintain infrastructure for AI/ML workloads, including containerization and orchestration using Docker and Kubernetes.
- Monitoring and Logging : Implement monitoring and logging solutions using Prometheus, Grafana, and ELK Stack to ensure visibility into AI/ML systems.
- CI/CD Pipelines : Develop and manage CI/CD pipelines using Jenkins, GitHub Actions, and Azure DevOps to automate testing, deployment, and scaling of AI/ML models.
- MLOps Integration : Integrate MLOps tools such as MLflow, Kubeflow, and Azure ML into existing infrastructure to streamline AI/ML workflows.
- Cloud Platform Management : Manage cloud platforms, including Azure (preferred), AWS, and GCP, to ensure scalability and reliability of AI/ML solutions.
- Scripting and Automation : Develop scripts and automation tools using Python, Bash, and PowerShell to streamline AI/ML workflows and infrastructure management.
Requirements :
- Total Experience : 4- 7 years of experience in DevOps, cloud engineering, or related fields.
- Relevant Experience : 5 years of experience in DevOps, with a focus on containerization, orchestration, and cloud platforms.
Primary Skills :
- DevOps Tools : Jenkins, GitHub Actions, Azure DevOps, Terraform
- Containerization & Orchestration : Docker, Kubernetes
- Monitoring & Logging : Prometheus, Grafana, ELK Stack
Secondary Skills :
- MLOps Tools : MLflow, Kubeflow, Azure ML, SageMaker
- Cloud Platforms : Azure (preferred), AWS, GCP
- Scripting & Automation : Python, Bash, PowerShell
(ref:hirist.tech)-
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