Top Benefits
About the role
Job Description
What is the opportunity?
As an experienced ML engineer, you will be responsible for building and managing ML and/or data platforms and pipelines for Data Science with appropriate data governance and security. You will work with data scientists and peer data engineers to actively solve business problems and delivering value using agile methodology. You will work with technical and business stakeholders to build and maintain an optimized and scalable ML / data pipeline. You will participate in the architecture review and approval process. You will also be responsible for working closely with data scientists in the area of data ingestion and feature engineering, establishing coding best practices, maintaining and managing technical documentation and incident triaging and resolution.
What will you do?
- As part of the ML / Data Engineering team, you will work on creating, developing and managing ML pipelines from experimentation to deployment of Data Science products. You will also be responsible for data sourcing, lineage, quality, transformation and storage.
- Build container based solutions, pipelines, APIs/Microservices and analytics portal for heterogeneous data sources on internal data lakes or cloud platforms
- Collaborate with Data scientists, Process Engineers and Business Stakeholders to develop ML / data pipelines, and assist with prescriptive and predictive analytics through consolidated data
- Execute Development and Integration activities (planning, execution, testing, deployment and post implementation support) of existing and new data and visualization Technologies (e.g. Omni-Channel reporting, Gamification/Visualization).
- Prepare data to be used for diagnostic/descriptive reporting and data science work.
- Identify and resolve data movement/transformation/processing bottlenecks
- Research emerging Data and Visualization technologies trends/best practices and propose solutions for Technology and Business partners.
- Mentor junior team members
What do you need to succeed?
Must Have:
- Bachelor’s degree in Computer Science, Engineering or equivalent from an accredited university
- 5+ years experience in building end to end ML and data pipelines
- Demonstrated leadership skills; ability to identify / foresee issues and to proactively recommend and build resilient solutions
- Advanced SQL knowledge and experience working with relational databases
- Experience in developing scalable, configurable applications using Python and application frameworks
- Knowledge of relevant security considerations for applications on cloud
- Knowledge of VMs and various MLOps platforms such as WandB, AWS SageMaker
- Knowledge of AWS
- 4+ years of hands-on experience in following key areas:
- Data engineering solutions: Logstash, Python, SQL Server, Kafka, Hadoop, Spark, Scala
- API: Flask, Node.JS, Django, and Microservices technologies
- Automation/DevOps: Github Actions, Airflow, UCD, Selenium and similar technologies
- Cloud technologies: Openshift, PCF, Docker, Kubernetes
- Git & code version management
Nice to Have
- Graduate degree in Computer Science, Engineering, or equivalent
- Supervised and Unsupervised Machine learning, Gen AI, Knowledge Graphs, Graph Database and Natural Language Processing
- Security frameworks: LDAP, Kerberos, OAuth 2.0, Vault integration
- Experience working in agile environment
- Tableau
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.
- 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
#LI-Post
#TechPJ
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.
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.
Top Benefits
About the role
Job Description
What is the opportunity?
As an experienced ML engineer, you will be responsible for building and managing ML and/or data platforms and pipelines for Data Science with appropriate data governance and security. You will work with data scientists and peer data engineers to actively solve business problems and delivering value using agile methodology. You will work with technical and business stakeholders to build and maintain an optimized and scalable ML / data pipeline. You will participate in the architecture review and approval process. You will also be responsible for working closely with data scientists in the area of data ingestion and feature engineering, establishing coding best practices, maintaining and managing technical documentation and incident triaging and resolution.
What will you do?
- As part of the ML / Data Engineering team, you will work on creating, developing and managing ML pipelines from experimentation to deployment of Data Science products. You will also be responsible for data sourcing, lineage, quality, transformation and storage.
- Build container based solutions, pipelines, APIs/Microservices and analytics portal for heterogeneous data sources on internal data lakes or cloud platforms
- Collaborate with Data scientists, Process Engineers and Business Stakeholders to develop ML / data pipelines, and assist with prescriptive and predictive analytics through consolidated data
- Execute Development and Integration activities (planning, execution, testing, deployment and post implementation support) of existing and new data and visualization Technologies (e.g. Omni-Channel reporting, Gamification/Visualization).
- Prepare data to be used for diagnostic/descriptive reporting and data science work.
- Identify and resolve data movement/transformation/processing bottlenecks
- Research emerging Data and Visualization technologies trends/best practices and propose solutions for Technology and Business partners.
- Mentor junior team members
What do you need to succeed?
Must Have:
- Bachelor’s degree in Computer Science, Engineering or equivalent from an accredited university
- 5+ years experience in building end to end ML and data pipelines
- Demonstrated leadership skills; ability to identify / foresee issues and to proactively recommend and build resilient solutions
- Advanced SQL knowledge and experience working with relational databases
- Experience in developing scalable, configurable applications using Python and application frameworks
- Knowledge of relevant security considerations for applications on cloud
- Knowledge of VMs and various MLOps platforms such as WandB, AWS SageMaker
- Knowledge of AWS
- 4+ years of hands-on experience in following key areas:
- Data engineering solutions: Logstash, Python, SQL Server, Kafka, Hadoop, Spark, Scala
- API: Flask, Node.JS, Django, and Microservices technologies
- Automation/DevOps: Github Actions, Airflow, UCD, Selenium and similar technologies
- Cloud technologies: Openshift, PCF, Docker, Kubernetes
- Git & code version management
Nice to Have
- Graduate degree in Computer Science, Engineering, or equivalent
- Supervised and Unsupervised Machine learning, Gen AI, Knowledge Graphs, Graph Database and Natural Language Processing
- Security frameworks: LDAP, Kerberos, OAuth 2.0, Vault integration
- Experience working in agile environment
- Tableau
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.
- 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
#LI-Post
#TechPJ
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.
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.