ML Ops Engineer

ML Ops Engineer
The Position is for a results-driven ML Ops Data Engineer with a solid foundation in Enterprise Data Operations (EDO) and hands-on experience in AWS Sage Maker Pipelines, ML flow, and other AWS services. The Position will play a key role in the following assignments:
1. Deploying models built by data scientist as batch models using Sage Maker pipelines & jobs OR step
functions/EMR.
2. Implementing ML Flow server for the Enterprise

 

Other Responsibilities:-
• Design, implement, and maintain scalable AWS Sage Maker Pipelines for training, validation, deployment,
and monitoring of machine learning models.
• Automate and operationalize ML workflows using tools like ML flow, Airflow, and AWS Lambda.
• Set up and manage ML flow tracking servers for experiment tracking and model registry.
• Build and optimize classification models using large-scale datasets stored in Amazon S3 and integrated
with AWS ML services.
• Ensure robust CI/CD pipelines for ML workflows using tools such as Code Pipeline/ GitHub Actions/ Azure DevOps.
• Maintain enterprise data quality, lineage, and governance standards in alignment with EDO frameworks.
• Integrate ML pipelines into broader enterprise data architecture, including data lakes, warehouses, and
business systems.

 

Required Skills:-
• Hands-on experience with AWS services, especially Sage Maker Pipelines, Lambda, and S3.
• Proficient in setting up and managing ML flow servers for model lifecycle tracking.
• Strong Python and SQL programming skills.
• Solid understanding of classification models and supervised learning techniques.
• Experience implementing data pipelines using cloud-native and containerized services (e.g., Docker, Kubernetes).
• Familiarity with data governance, lineage, and metadata management (e.g., Collibra, Informatica, Alation)
• Strong knowledge of Enterprise Data Operations (EDO) practices.

 

Good to Have Skills:-
• Experience in Insurance Domain
• Experience deploying real time models on Sage Maker endpoints.
• Experience with AWS services such as IAM, SNS, CloudWatch
• Experience with snowflake databases and relational data sets.

 

Qualification:- BACHELOR OF COMPUTER SCIENCE