Senior ML Engineer, ML Platform - GFT
About The Position
The opportunity is with Global Functions Technology (GFT), part of RBC’s Technology and Operations division. GFT collaborates with partners across the company to deliver innovative and transformative IT solutions for clients in Risk, Finance, HR, CAO, Audit, Legal, Compliance, Financial Crime, Capital Markets, Personal and Commercial Banking, and Wealth Management. GFT also leads the development of digital tools and platforms to enhance collaboration. The role is for an MLOps Engineer to design and build a production-grade machine learning pipeline for financial risk model training and inference. This pipeline will support model training/testing/inference using Python and PySpark on public cloud (AWS) and on-premises infrastructure. This role is ideal for an engineer with Python programming, system design, and cloud engineering skills, combined with a solid understanding of the machine learning model lifecycle. The engineer will 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.
Requirements
- Bachelor’s degree in computer science, engineering, data science, or related quantitative and technical fields.
- 3+ years of experience in software engineering, data engineering, or MLOps.
- 1+ year experience working with AWS components
- Experience working with containers and infrastructure automation.
- Experience working with Linux systems, shell scripting, and environment management.
- Knowledge of AWS data and ML services e.g., S3, EMR, Lambda, Step Functions, ECS/EKS, SageMaker, CloudWatch, IAM.
- Understanding of model lifecycle management from training and testing to deployment, monitoring, and retraining.
- Experience with CI/CD practices, using tools like GitHub Actions, Jenkins, or CodePipeline.
- Familiarity with hybrid deployment environments (AWS and on-prem) and related networking/security considerations.
- Knowledge of Python scripting for automation and ML workflow integration.
- Knowledge of PySpark for distributed data processing and model training.
Nice To Haves
- AWS Certified Machine Learning Engineer Associate, or Certified Solution Architect Associate, or CloudOps/SysOps Engineer Associate
- AWS Certified Cloud Practitioner - Amazon Web Services
- Experience implementing model monitoring and drift detection.
- Familiarity with distributed training and parallel compute frameworks (Ray, Spark, Dask).
- Experience with feature stores, data lineage, or metadata tracking systems.
- Exposure to financial risk modeling workflows.
Responsibilities
- Design and implement end-to-end reusable MLOps pipelines with a team of engineers to train, test, register, and deploy 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 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, Cloudera Data Platform, or similar.
- Manage model artifacts, dependencies, and environments across AWS and on-premis.
- 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.
Benefits
- bonuses
- flexible benefits
- competitive compensation
- commissions
- 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
- Flexible work/life balance options
- Opportunities to do challenging work
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What This Job Offers
Job Type
Full-time
Career Level
Senior
