MLOps Engineer — AWS SageMaker

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