Job Title

MLOps Engineer — AWS SageMakerClient: A large global enterprise (name not disclosed)Location: IndiaWork Model: 100% RemoteContract: 6 months (initial) with possibility of extensionStart Date: ASAPEngagement: Full-time / Long-term contractRole OverviewYou will work within a global data & analytics team to design, deploy, and maintain robust ML pipelines using AWS SageMaker and associated cloud services. The role requires strong experience in production-grade MLOps, automation, and cloud engineering.Key ResponsibilitiesBuild, deploy, and maintain ML models using AWS SageMaker (Pipelines, Endpoints, Model Registry)Develop automated CI/CD workflows using CodePipeline, CodeBuild, or GitHub ActionsImplement model monitoring, logging, and drift detection (CloudWatch, SageMaker Model Monitor)Create and maintain infrastructure using Terraform or CloudFormationManage secure, scalable, cost-optimized AWS environments (IAM, VPC, networking)Collaborate with data scientists, cloud engineering teams, and solution architectsTroubleshoot issues in high-availability, production ML setupsRequired Experience4–8 years total experience in MLOps / ML EngineeringHands-on experience with SageMaker in enterprise-scale environmentsStrong Python skills & familiarity with ML frameworksExperience with Docker, Kubernetes (EKS preferred)Experience building CI/CD pipelinesDeep practical knowledge of AWS ecosystemNice to HaveExperience implementing model governanceExperience with multi-model endpointsFamiliarity with enterprise security standards and compliance