MLOps Engineer — AWS SageMaker
1 week ago
MLOps Engineer — AWS SageMaker Client: A large global enterprise (name not disclosed) Location: India Work Model: 100% Remote Contract: 6 months (initial) with possibility of extension Start Date: ASAP Engagement: Full-time / Long-term contract Role Overview You 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 Responsibilities Build, deploy, and maintain ML models using AWS SageMaker (Pipelines, Endpoints, Model Registry) Develop automated CI/CD workflows using CodePipeline, CodeBuild , or GitHub Actions Implement model monitoring, logging, and drift detection (CloudWatch, SageMaker Model Monitor) Create and maintain infrastructure using Terraform or CloudFormation Manage secure, scalable, cost-optimized AWS environments (IAM, VPC, networking) Collaborate with data scientists, cloud engineering teams, and solution architects Troubleshoot issues in high-availability, production ML setups Required Experience 4–8 years total experience in MLOps / ML Engineering Hands-on experience with SageMaker in enterprise-scale environments Strong Python skills & familiarity with ML frameworks Experience with Docker, Kubernetes (EKS preferred) Experience building CI/CD pipelines Deep practical knowledge of AWS ecosystem Nice to Have Experience implementing model governance Experience with multi-model endpoints Familiarity with enterprise security standards and compliance
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