ML Data Engineer
RBC CENTRE, 155 WELLINGTON ST W:TORONTO, Canada
CAD 65K-110K (estimate) Mid-level Full Time
Tasks
- Architect data foundation for AI and BI analytics
- Automate data preparation and integration tasks
- Build and maintain feature stores and training datasets
- Collaborate with stakeholders to translate data requirements
- Contribute to data governance and security compliance
- Create and maintain data assets across Dev UAT and Production
- Develop and maintain integrations for model serving
- Develop and optimize data pipelines for ML lifecycle
- Implement data quality frameworks and automated testing
- Implement monitoring logging and observability for pipelines and ML models
- Ingest transform and serve structured and unstructured data
- Integrate AI capabilities with production systems via APIs
- Support CI CD infrastructure as code and automated testing
- Work in an agile framework
Perks/Benefits
- Coaching mentorship and growth opportunities
- Flexible benefits
- Flexible work-life balance
- Stock options
Skills/Tech-stack
APIs | AWS | Apache Spark | Azure | Azure DevOps | CI/CD | Cloud platform | CloudFormation | Data Governance | Data Lakehouse | Data Modeling | Data Pipelines | Data Quality | Data Security | Data Warehousing | Databricks | ETL | Feature Engineering | Feature Stores | Generative AI | GitHub Actions | Google Cloud | Google Cloud Platform | Infrastructure as Code | Jenkins | Kafka | Kinesis | LLM | LLM serving | MLOps | Machine Learning | Model Monitoring | Model Serving | Python | RAG | Retrieval-Augmented Generation | SQL | Snowflake | Streaming Data | Terraform | Vector Databases | “as-code”
Education
Roles
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