• Project overview
• Implement a complete DevOps and MLOps infrastructure for the EyeFish platform covering deployment, monitoring and automation.
• Scope includes CI/CD pipelines for backend, frontend and AI microservices, containerization and orchestration, AWS deployments, monitoring, logging and MLOps workflows for model deployment and continuous training.
• Main objectives & deliverables
• Design and implement the complete DevOps architecture for the EyeFish platform.
• Create CI/CD pipelines (backend, frontend, AI services), automate deployments on AWS, and implement real-time infrastructure monitoring and alerting.
• Optimize performance and reduce cloud costs, test deployments in the EyeFish environment, prepare technical documentation and perform the final demonstration.
• Responsibilities / Tasks
• Implement containerization and orchestration using Docker and Kubernetes; set up CI/CD (GitHub Actions / GitLab CI) for multi-service pipelines.
• Deploy and automate infrastructure on AWS (EC2, S3, IAM, CloudWatch, ECS/EKS) and integrate monitoring (Prometheus, Grafana) and centralized logs.
• Define and implement MLOps workflows: model deployment, continuous training, inference pipeline optimization, and internal operational workflows with standardized documentation.
• Required skills & technologies
• Docker, Docker Compose; basics of Kubernetes; Linux and Bash scripting.
• CI/CD experience (GitHub Actions or GitLab CI); AWS experience (EC2, S3, IAM, CloudWatch, ECS/EKS); monitoring tools (Prometheus, Grafana) and centralized logging.
• Practical details & how to apply
• Internship tasks include hands-on implementation, testing in EyeFish environment, and producing technical documentation and a final demo.
• Apply via the provided link below.

Apply here: https://lnkd.in/d3jkmmJC