GE
GetinzAI/ML Engineer
Innovation Engineer responsible for AI - driven solutions at a digital commerce company. Focused on prototyping, exploring technologies, and shaping technology strategy.
About the role
- 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.
- Ensure secure, compliant cloud deployments (IAM, RBAC, encryption, network security).
Requirements
- Bachelor’s or Master’s in Computer Science, Machine Learning, or related field.
- 5+ years of professional experience in ML engineering, MLOps, or data-pipeline development.
- Proven ability to design and automate end-to-end ML pipelines in the cloud.
- Strong Python and SQL skills.
- Experience integrating ML systems with enterprise data sources (Oracle, Snowflake).
- Familiar with containerized deployments, workflow orchestration, and CI/CD.
- Understanding of model lifecycle management, versioning, and deployment best practices.
Benefits
- Flexible work arrangements
- Professional development opportunities
Job title
Job type
Experience level
Salary
Not specified
Degree requirement
Tech skills
Location requirements
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