mokSa.ai - DevOps Engineer - Cloud Infrastructure

Responsibilities

• Design, deploy, and manage cloud-based infrastructure for machine learning workloads, ensuring scalability, reliability, and performance.
• Collaborate with data scientists and machine learning engineers to understand model requirements and operationalize machine learning pipelines.
• Implement CI/CD pipelines for automating the training, testing, and deployment of machine learning models.
• Develop and maintain monitoring and alerting systems to track the performance and health of deployed machine learning models.
• Optimize resource utilization and cost-effectiveness of cloud resources used for machine learning tasks.
• Implement security best practices to protect sensitive data and machine learning models in cloud environments.
• Work closely with software development teams to integrate machine learning models into production applications.
• Troubleshoot and resolve issues related to infrastructure, deployment, and performance of machine learning systems.
• Stay updated with the latest advancements in cloud computing, DevOps tools, and machine learning technologies.
• Document processes, procedures, and configurations related to machine learning infrastructure and deployment pipelines.
  

Requirements

• Bachelors degree in Computer Science or related field.
• 2+ Experience with cloud platforms (AWS) and DevOps practices.
• Proficiency in scripting languages (Python, Shell scripting).
• Familiarity with containerization (Docker, Kubernetes) and machine learning frameworks.
• Strong problem-solving skills and ability to work in a fast-paced environment.
  

Preferred Qualifications

• Certification in AWS and Kubernetes are Preferred
• Experience with infrastructure automation tools (Terraform, Ansible).
• Knowledge of machine learning deployment tools (MLflow, Kubeflow).
• Familiarity with cybersecurity principles for cloud-based systems.
  

Perks & Benefits

• Salary is not a constraint to right candidate - as per market value