DevOps Engineer for AI/ML Infrastructure

5 days ago


Bengaluru, Karnataka, India Creenosolutions Pvt Ltd Full time

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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