Responsibilities
- Design and implement reusable end-to-end MLOps pipelines for model training, testing, registration, and deployment.
- Automate model lifecycle workflows including versioning, promotion, approval, deprecation, metadata, lineage, and reproducibility.
- Develop and integrate model registries such as MLflow, SageMaker Model Registry, or a custom solution.
- Orchestrate data and training workflows using Airflow, AWS Step Functions, Stonebranch, or Prefect.
- Implement CI/CD pipelines with GitHub Actions, Jenkins, or AWS CodePipeline.
- Build performant and scalable data preparation and training scripts using Python and PySpark on AWS EMR, Cloudera Data Platform, or similar systems.
- Manage model artifacts, dependencies, and environments across AWS and on-premises infrastructure.
- Implement structured logging, metrics, model performance tracking, observability, and auditability.
- Collaborate with DevOps and data engineering teams on secure integration, data governance, and production readiness.
Requirements
- Bachelor’s degree in computer science, engineering, data science, or a related quantitative or technical field.
- At least 3 years of experience in software engineering, data engineering, or MLOps.
- At least 1 year of experience working with AWS components.
- Experience with containers, infrastructure automation, Linux systems, shell scripting, and environment management.
- Knowledge of AWS data and machine learning services including S3, EMR, Lambda, Step Functions, ECS/EKS, SageMaker, CloudWatch, and IAM.
- Understanding of the machine learning model lifecycle from training and testing through deployment, monitoring, and retraining.
- Experience with CI/CD practices and tools such as GitHub Actions, Jenkins, or CodePipeline.
- Familiarity with hybrid AWS and on-premises deployment environments and related networking and security considerations.
- Knowledge of Python scripting for automation and machine learning workflow integration.
- Knowledge of PySpark for distributed data processing and model training.
- AWS Certified Machine Learning Engineer Associate, Certified Solutions Architect Associate, CloudOps/SysOps Engineer Associate, or AWS Certified Cloud Practitioner certification is preferred.
- Experience with model monitoring, drift detection, distributed training, parallel compute frameworks such as Ray, Spark, or Dask, feature stores, data lineage, metadata tracking systems, or financial risk modeling workflows is preferred.
Benefits
- Comprehensive Total Rewards Program including bonuses and flexible benefits, competitive compensation, commissions, and stock where applicable.
- Development support through coaching and management opportunities.
- Opportunity to make a difference and lasting impact.
- Dynamic, collaborative, progressive, and high-performing team environment.
- World-class training program in financial services.
- Flexible work/life balance options.
- Full-time regular salaried employment in Vancouver, Canada, with 37.5 working hours per week.
Tech Stack
Categories
About RBC
Royal Bank of Canada is a global financial institution with a purpose-driven, principles-led approach to delivering leading performance. Our success comes from the 94,000+ employees who leverage their imaginations and insights to bring our vision, values and strategy to life so we can help our clients thrive and communities prosper. As Canada's biggest bank and one of the largest in the world, based on market capitalization, we have a diversified business model with a focus on innovation and providing exceptional experiences to our more than 17 million clients in Canada, the U.S. and 27 other countries. Learn more at rbc.com. We are proud to support a broad range of community initiatives through donations, community investments and employee volunteer activities. See how at www.rbc.com/community-social-impact. http://rbc.com/legalstuff. La Banque Royale du Canada est une institution financière mondiale définie par sa raison d'être, guidée par des principes et orientée vers l'excellence en matière de rendement. Notre succès est attribuable aux quelque 94 000+ employés qui mettent à profit leur créativité et leur savoir faire pour concrétiser notre vision, nos valeurs et notre stratégie afin que nous puissions contribuer à la prospérité de nos clients et au dynamisme des collectivités. Selon la capitalisation boursière, nous sommes la plus importante banque du Canada et l'une des plus grandes banques du monde. Nous avons adopté un modèle d'affaires diversifié axé sur l'innovation et l'offre d'expériences exceptionnelles à nos plus de 17 millions de clients au Canada, aux États Unis et dans 27 autres pays. Pour en savoir plus, visitez le site rbc.com/francais Nous sommes fiers d'appuyer une grande diversité d'initiatives communautaires par des dons, des investissements dans la collectivité et le travail bénévole de nos employés. Pour de plus amples renseignements, visitez le site www.rbc.com/collectivite-impact-social. https://www.rbc.com/conditions-dutilisation/