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