Job Description

Job Title: SSE - AWS MLops engineer Primary Skill: Sagemaker, Lambda, Python Location: Hyderabad/Pune/Coimbatore Mode of work: 5 Days Work from Office Experience: 4 to 7 years Job Summary:As a MLops Engineer, you will play a crucial role in developing and implementing robust MLops infrastructures, ensuring data integrity, optimizing ML workflows, and enabling advanced analytics capabilities. You will work closely with cross-functional teams to understand business requirements, design CICD solutions, and collaborate with DS team across the organization.Responsibilities Model Deployment : Deploy, monitor, and manage machine learning models in AWS environments (SageMaker, EC2, Lambda). Automation : Develop and maintain CI/CD pipelines for ML workflows using tools like Gitlab,AWS CodePipeline, CodeBuild, and Jenkins. Infrastructure Management: Design and manage scalable, reliable, and cost-effective AWS infrastructure for ML workloads (S3, RDS, DynamoDB, etc.). Monitoring and Logging: Implement monitoring and logging solutions to ensure models are performing as expected (CloudWatch, Sagemaker Model Monitor). Collaboration : Work closely with Data Scientists and DevOps teams to integrate ML models into production environments. RequirementsMust Have: 4+ years of experience in MLOps, DevOps, or related fields. Should be able to drive the requirements, follow-up, collaboration with cross teams Hands-on experience with AWS services like SageMaker, EC2, Lambda, S3, and RDS. Proficiency in Python and experience with ML frameworks like TensorFlow, PyTorch, or Scikit-Learn. Experience with CI/CD tools and best practices Familiarity with Infrastructure as Code (IaC) using tools like Terraform or AWS CloudFormation. Knowledge of data engineering tools and practices. Knowledge of Kubernetes or Docker. Effective communication and collaboration skills, with the ability to effectively interact with stakeholders at all levels.