Cloud – MLOps Engineer

We are seeking a highly skilled Cloud MLOps Engineer to design implement and manage scalable cloud-based machine learning infrastructure on AWS. The ideal candidate will have strong expertise in AWS cloud architecture MLOps pipeline automation and Large Language Models (LLMs) along with solid DevOps and CI/CD capabilities. This role involves developing automated secure and efficient workflows to support AI-driven applications enabling continuous training deployment and monitoring of models in production environments.

Roles and Responsibilities

• Design develop and maintain robust AWS cloud infrastructure to support large-scale data-intensive applications.
  

• Architect and implement scalable solutions using AWS services including EC2 S3 Lambda RDS IAM VPC and CloudFormation.
  

• Develop and manage MLOps pipelines to automate model training validation deployment and monitoring processes.
  

• Ensure seamless integration between data pipelines and machine learning workflows for efficient model lifecycle management.
  

• Implement and optimize LLM-based solutions including fine-tuning pre-trained models and deploying AI-driven services in production.
  

• Build and maintain CI/CD pipelines using Jenkins GitLab CI CircleCI or AWS CodePipeline to automate testing and deployment.
  

• Adopt Infrastructure as Code (IaC) practices with Terraform AWS CDK or CloudFormation for consistent repeatable infrastructure provisioning.
  

• Ensure high standards of security scalability and performance across all cloud environments.
  

• Monitor and analyze cloud environments using AWS CloudWatch ELK Stack Prometheus or Grafana to ensure operational stability.
  

• Collaborate with data scientists developers and architects to deliver reliable and automated MLOps solutions.
  

• Mentor and guide junior engineers promoting best practices and continuous improvement within the engineering team.
  

• Drive technical innovation exploring new tools frameworks and AWS features to enhance AI and cloud capabilities.
  

Requirements

• Bachelors or Masters degree in Computer Science Data Engineering or a related field.
  

• 5 years of experience in cloud engineering or DevOps with at least 2 years in MLOps and model deployment environments.
  

• Proven hands-on experience with AWS cloud infrastructure and core services (EC2 S3 RDS Lambda VPC IAM CloudFormation).
  

• Strong proficiency in MLOps frameworks and pipeline orchestration for training validation and deployment automation.
  

• Experience working with Large Language Models (LLMs) including fine-tuning optimization and production deployment.
  

• Solid understanding of CI/CD processes using Jenkins GitLab CI or AWS CodePipeline.
  

• Practical experience with Infrastructure as Code (IaC) tools such as Terraform AWS CDK or CloudFormation.
  

• Knowledge of monitoring and observability tools (CloudWatch ELK Prometheus Grafana).
  

• Familiarity with security best practices in AWS and DevOps environments.
  

• Excellent problem-solving analytical and communication skills with a passion for automation and AI innovation.
  

Requirements