Senior MLOps Engineer designing and maintaining data and machine learning pipelines for retail technology. Integrating multiple cloud services and ensuring efficient, secure deployments in a hybrid work model.
Responsibilities
Build and automate ML pipelines for data preparation, training, inference, and retraining.
Develop and maintain data pipelines between Oracle ERP, Snowflake, and cloud environments.
Create Kedro-based modular pipelines for reusable and maintainable workflows.
Use AWS Glue, DMS, Athena, and dbt for ETL and data transformation.
Manage AWS Batch and Fargate workloads for scalable model training and inference.
Integrate advanced data-science and forecasting libraries into production workflows.
Implement CI/CD pipelines for ML and data workflows (GitHub Actions, Jenkins, etc).
Use MLflow for experiment tracking, model registry, and artifact management.
Build and maintain Dockerized environments via AWS EC2, ECR, and Batch.
Collaborate with data scientists to operationalize models and optimize performance.
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