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
- Robust 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.

📌 Staff ML Data Engineer Toronto
🏢 ODAIA
📍 Toronto