Data & AI Engineer

RBCToronto, ON
Onsite

About The Position

The Next Best Action team at RBC, part of the Personal Banking organization, is responsible for running day-to-day marketing campaigns and experiments for banking clients. The Data Innovation team maintains the ecosystem that drives the Next Best Action initiative, which includes big data pipelines, machine learning models, full stack applications, and microservices. This role is for a Data & ML Engineer to contribute to and build upon this ecosystem, collaborating with technology and business partners across the bank. It offers an opportunity to learn about a production system within the marketing sector, experience a unique blend of a start-up within a large organization, and to learn and flex into different areas of the ecosystems or additional projects of interest.

Requirements

  • 2+ years in software engineering or software development with a language like Python, Java, Scala or equivalent.
  • Experience of SQL and relational databases like MySQL, Postgres, SQL server or equivalent.
  • A curiosity and passion for continuous learning and helping others.
  • Bachelor’s degree or master’s degree in computer science, software engineering, data engineering, machine learning engineering or equivalent field.

Nice To Haves

  • Experience with big data processes (Spark, Airflow) including batch processing and/or real-time streaming technologies is preferred.
  • Experience with Agentic AI and LLMs are an asset.
  • Experience with database technologies such as noSQL, graph databases, vector databases, etc. is an asset.
  • Knowledge of public cloud (Azure, AWS, GCP, OpenShift or equivalent) platforms and development of applications in multi-cloud, hybrid environments is preferred.
  • Experience simplifying and automating work and making things better for clients.
  • Experience with continuous integration and development and/or MLOps tools is an asset.
  • Experience in financial services industry with broad understanding of marketing, product management, sales, finance, pricing, and risk management is an asset.

Responsibilities

  • Evolve the existing machine learning system to be make machine learning processes scale to be quicker, more reliable and if applicable autonomous or semi-autonomous.
  • Deliver data driven solutions alongside data scientists and business stakeholders to help monitor and assess quality on the end-to-end system flow for machine learning development including data ingestion, feature engineering, model training, model inference, model serving and model monitoring.
  • Responsible for researching new capabilities and technologies to drive innovation as appropriate including Agentic AI and GenAI.
  • Manage, optimize, oversee and monitor data & model pipelines as well as the UI used to inform client decisions related to Next Best Action recommendations.

Benefits

  • A comprehensive Total Rewards Program including bonuses and flexible benefits, competitive compensation, commissions, and stock where applicable
  • Leaders who support your development through coaching and managing opportunities
  • Ability to make a difference and lasting impact
  • Work in a dynamic, collaborative, progressive, and high-performing team
  • A world-class training program in financial services
  • Opportunities to do challenging work
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