Senior DevOps Engineer - Docker/Kubernetes

Job Description : We are looking for a skilled DevOps Engineer with a strong background in AI/ML and extensive experience with AWS, Kubernetes, and container-based architectures. If you have a passion for building robust infrastructure and supporting advanced machine learning applications, we'd love to have you on our : - Infrastructure Management : Design, deploy, and manage scalable infrastructure on AWS, including services like EBS (Elastic Block Store) and GPU servers for AI/ML workloads. - Kubernetes & EKS : Set up and maintain Kubernetes clusters using Amazon EKS, ensuring high availability and optimal performance. - CI/CD Pipelines : Develop and manage continuous integration and continuous deployment pipelines to streamline application updates and deployments. - Microservices Architecture : Support and maintain a microservices-based architecture, ensuring seamless integration and communication between services. - Containerization : Utilize Docker and other container technologies to package and deploy applications consistently across environments. - Monitoring & Logging : Implement monitoring and logging solutions to track system performance, identify issues, and ensure reliability. - Security : Ensure the security of the infrastructure by implementing best practices and managing access controls. - Collaboration : Work closely with AI/ML engineers, software developers, and other team members to support their infrastructure and deployment needs. - Automation : Automate repetitive tasks to improve efficiency and reduce the potential for human error. - Troubleshooting : Diagnose and resolve infrastructure and deployment issues promptly to minimize : - - Experience : 5 years of experience in DevOps or a similar role, preferably within AI/ML or technology-focused companies. - AWS Expertise : Deep understanding of AWS services , including EC2, EBS, S3, RDS, and especially EKS (Elastic Kubernetes Service). - Kubernetes : Hands-on experience with Kubernetes for container orchestration and management. - Containerization : Proficiency with Docker and container-based deployment strategies. - Microservices: Experience working with microservices architecture and managing inter-service communication. - CI/CD Tools : Familiarity with CI/CD tools such as Jenkins, GitLab CI, CircleCI, or similar. - Scripting : Strong scripting skills in languages like Python, Bash, or similar for automation tasks. - GPU Servers : Experience managing and optimizing GPU servers for AI/ML workloads is highly desirable. - Monitoring Tools : Knowledge of monitoring and logging tools like Prometheus, Grafana, ELK Stack, or similar. - Problem-Solving : Excellent problem-solving skills and the ability to troubleshoot complex infrastructure issues. - Team Player : Strong communication skills and the ability to work effectively within a collaborative team environment. Preferred Qualifications : - Education : Bachelor's or Master's degree in Computer Science, Engineering, or a related field. - Certifications : AWS Certified DevOps Engineer, Kubernetes Certified Administrator, or similar certifications. - Automation Tools : Experience with Infrastructure as Code (IaC) tools like Terraform or CloudFormation. - Security : Knowledge of security best practices and experience implementing security measures in cloud environments. - AI/ML Exposure : Previous experience working in AI/ML projects or with machine learning frameworks. (ref:hirist.tech)

Location: bangalore, IN

Posted Date: 11/25/2024