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 (Winnipeg)
🏢 ODAIA
📍 Winnipeg