DevOps Engineer for AI/ML Infrastructure
5 days ago
Job Overview
Creenosolutions Pvt Ltd is seeking an experienced DevOps Engineer to join our team. As a key member of our infrastructure team, you will be responsible for designing and deploying scalable infrastructure on AWS, including services like EBS (Elastic Block Store) and GPU servers for AI/ML workloads.
About the Role
- Design and deploy scalable infrastructure on AWS, including EC2, EBS, S3, RDS, and especially EKS (Elastic Kubernetes Service).
- Set up and maintain Kubernetes clusters using Amazon EKS, ensuring high availability and optimal performance.
- Develop and manage continuous integration and continuous deployment pipelines to streamline application updates and deployments.
- Support and maintain a microservices-based architecture, ensuring seamless integration and communication between services.
- Utilize Docker and other container technologies to package and deploy applications consistently across environments.
- Implement monitoring and logging solutions to track system performance, identify issues, and ensure reliability.
- Ensure the security of the infrastructure by implementing best practices and managing access controls.
- Work closely with AI/ML engineers, software developers, and other team members to support their infrastructure and deployment needs.
- Automate repetitive tasks to improve efficiency and reduce the potential for human error.
- Diagnose and resolve infrastructure and deployment issues promptly to minimize downtime.
Requirements
- 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.
What We Offer
The estimated salary for this role is $150,000 - $220,000 per year, depending on experience and location.
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