About Position:
We are seeking an experienced AWS Sage Maker Engineer to design and build scalable MLOps platforms and machine learning pipelines on AWS. The role focuses on enabling end-to-end ML lifecycle management including model development, deployment, monitoring, and automation. The ideal candidate will have solid expertise in Sage Maker, cloud-native architecture, and Dev Ops practices, along with the ability to collaborate with data science teams to productionize ML use cases efficiently.
Role : AWS Sage Maker Engineer
Location: All Persistent Location
Experience: 8-12 years
Job Type: Full Time Employment
What You'll Do:
Design and implement end-to-end MLOps pipelines on Amazon Sage Maker for training, validation, deployment, and monitoring
Build Dev Ops automation to provision and manage ML infrastructure across environments
Develop Python-based tools and frameworks to standardize ML workflows and platform operations
Implement CI/CD pipelines for ML models, feature pipelines, and Sage Maker jobs
Automate model packaging, versioning, promotion,



and rollback across Dev/Test/Prod
Enforce security, governance, and compliance controls for ML platforms and data access
Optimize Sage Maker workloads for performance, scalability, and cost efficiency
Integrate Sage Maker with AWS services such as S3, IAM, Cloud Watch, Event Bridge, and ECR
Implement monitoring and alerting for model performance, drift, failures, and infrastructure health
Collaborate with data science and engineering teams to productionize ML use cases
Troubleshoot complex platform, pipeline, and deployment issues in distributed ML systems
Drive platform best practices, documentation, and continuous improvement initiatives
Expertise You'll Bring:
8-12 years of hands-on experience in Dev Ops, MLOps, or ML platform engineering
Strong expertise with Amazon Sage Maker for building and operating ML pipelines
Advanced proficiency in Python for automation, pipeline development, and tooling
Deep experience

📌 Aws sagemaker engineer (Pune)
🏢 Persistent Systems
📍 Pune