Lead Cloud MLOps Engineer, GFT

What is the opportunity?

Are you a talented, creative, and results-driven professional who thrives on delivering high-performing applications? Come join us!

Job Description

GFT (Global Functions Technology) is part of RBC’s Technology and Operations division. GFT collaborates with partners across the company to deliver innovative and transformative IT solutions. Our clients include Risk, Finance, HR, CAO, Audit, Legal, Compliance, Financial Crime, Capital Markets, Personal and Commercial Banking, and Wealth Management. We also lead the development of digital tools and platforms to enhance collaboration.

We are looking for a highly skilled MLOps Engineer to design and build a production-grade Machine Learning pipeline for financial risk model training and inference. The pipeline will support model training / testing / inference using Python and PySpark on public cloud (AWS) and on-premise infrastructure. This role combines strong Python and cloud engineering skills with a solid understanding of machine learning model lifecycle management from data preparation through training, validation, registration, and operational inference. You’ll collaborate with data scientists, DevOps, and risk IT teams to build a reliable, automated, and auditable MLOps platform that meets enterprise standards for security, governance, and scalability.

What will you do?

• Design and implement end-to-end MLOps pipelines to train, test, register, and deploy credit risk machine learning models.
• Build and automate model lifecycle management workflows including versioning, promotion, approval, and deprecation.
• Develop and integrate a model registry (e.g., MLflow, SageMaker Model Registry, or a custom solution) to manage model metadata, lineage, and reproducibility.
• Orchestrate data and training workflows using tools such as Airflow, AWS Step Functions, stonebranch, or Prefect.
• Implement CI / CD pipelines using GitHub Actions, Jenkins, or AWS CodePipeline, ensuring consistent and automated deployment processes.
• Build data preparation and training scripts in Python and PySpark, optimized for performance and scalability on AWS EMR or similar clusters.
• Manage model artifacts, dependencies, and environments across AWS and on-premise contexts.
• Ensure strong observability and auditability through structured logging, metrics, and model performance tracking.
• Collaborate with DevOps and data engineering teams to ensure secure integration, data governance, and production readiness.

What do you need to succeed?

Must Have :

Required Experience

Required Certifications (or Equivalent Experience)

Nice to Have

What’s in it for you?

We thrive on the challenge to be our best, progressive thinking to keep growing, and working together to deliver trusted advice to help our clients thrive and communities prosper. We care about each other, reaching our potential, making a difference to our communities, and achieving success that is mutual.

RBC is presently inviting candidates to apply for this existing vacancy. Applying to this posting allows you to express your interest in this current career opportunity at RBC. Qualified applicants may be contacted to review their resume in more detail.

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