Build ML-ready infrastructure and scalable pipelines as a Staff ML Data Engineer with RBC Wealth Management in Toronto, supporting AI and analytics.
This Staff-level role bridges machine learning and traditional data engineering across Wealth Management Data & AI. You will prepare feature stores, training datasets, and production data infrastructure while supporting analytics-ready pipelines. Your work contributes to investment capabilities, operational improvements, client experience, and executive decision-making.
Key Responsibilities: Architect reliable data foundations for AI/ML and BI workloads
Build feature stores, training datasets, and ML infrastructure
Develop pipelines across ingestion, feature engineering, and model serving




Implement MCP and API integrations with production systems
Monitor pipelines and models for reliability and compliance
Requirements: Bachelor’s degree in a related technical field
Five-plus years in ML data engineering or related roles
Solid Python, SQL, MCP, API, and pipeline experience
Experience with Databricks, Snowflake, Spark, and cloud services
Knowledge of feature stores, RAG, vector databases, and LLM serving
Apply staff-level data engineering expertise across Python, SQL, ML infrastructure, and modern cloud platforms at RBC Wealth Management.

#J-18808-Ljbffr

📌 Staff ML Data Engineer Toronto (Ontario)
🏢 ODAIA
📍 Ontario