Machine Learning Platform Engineer (Cloud Data)

What's the opportunity?

Are you interested in the opportunity to work as a Machine Learning Platform Engineer on the Cloud Data and ML platform engineering team at RBC Borealis? Our team is looking for experienced ML Platform Engineers with experience in full stack development to contribute to our platform services, API, and enablement of Azure services for our customers.

RBC Borealis Cloud Data and ML platform engineering team is responsible for enabling Public Cloud for our internal data engineering and data scientists at RBC. We work with 100s of developers and data scientists across RBC to leverage Azure to accelerate their work across the full end to end data and machine learning lifecycle. This is a unique opportunity to grow in the world of machine learning infrastructure and work with a team of passionate individuals committed to the mission of bringing ML to enterprise.

At RBC Borealis, you’ll be joining a team that works directly with leading researchers in machine learning, has access to rich and massive datasets, and offers the computational resources to support ongoing development in areas such as reinforcement learning, unsupervised learning and computer vision. You can find out more about our research areas at rbcborealis.com.

Your responsibilities include:

• Performing complex application programming activities, including coding, testing, debugging, documenting, maintaining, and modifying complex applications programs

• Create and review technical design documents, understand how the design will be used in the code development process, and facilitate meetings to design, troubleshoot, and execute projects

• Develop APIs and microservices to support Enterprise Machine Learning Platform client initiatives

• Present technical topics at regular sprint meetings and manage low-level planning of work packages

• Designing, building, and optimizing machine learning deployment tools and automation systems that operate the business’s data and ML applications

• Designing and implementing best practices and standards for data and machine learning pipelines across the organization

• Supporting applications and projects with infrastructure design decision, and monitoring solution

• Building a highly scalable, resilient cloud platform for hosting machine learning systems using state-of-the-art technologies.

You're our ideal candidate if you have:

• Strong full stack development experience using frontend frameworks such as VueJS/React and backend languages such as Python or Golang

• Strong platform engineering experience and experience implementing scalable distributed systems

• Working with building and maintaining DevOps pipeline such as Jenkins, GitHub actions

• Previous experience with MLOps orchestration tools such as AirFlow, KubeFlow, Dagster, Flyte, or MetaFlow

• Experience implementing monitoring solutions to identify system bottlenecks and production issues

• Hands-on experience building and deploying hybrid environments on-prem and major cloud environments, such as AWS and Azure

• Strong experience implementing Infrastructure as Code in Terraform, Cloudformation, or Azure Resource Manager (ARM) Templates

• Experience working with Databricks, especially Azure Databricks

• Data engineering knowledge is helpful but not required for the role

What's in it for you?

• Become part of a team that thinks progressively and works collaboratively. We care about seeing each other reach full potential

• A comprehensive Total Rewards Program including bonuses and flexible benefits, competitive compensation, commissions, and stock options where applicable

• Leaders who support your development through coaching and managing opportunities

• Ability to make a difference and lasting impact from a local-to-global scale.

About RBC Borealis

RBC Borealis is the driving force behind Royal Bank of Canada’s AI and data innovation. As part of Canada’s largest financial institution, we bring together a team of architects, engineers, scientists, and product experts on a mission to revolutionize finance through world-class research, solutions, and a resilient data platform. With locations across Toronto, Waterloo, Montreal, Calgary, and Vancouver, we’re at the forefront of AI research and platform development. With a focus on cutting-edge research in areas like time series forecasting, causal machine learning, and responsible AI, we are seamlessly integrating AI research and data engineering, to solve critical challenges in the financial industry. We are building intelligent, and scalable, data-driven solutions that will help communities thrive and drive innovation for our customers across the bank.

Inclusion and Equal Opportunity Employment

RBC is an equal opportunity employer committed to diversity and inclusion. We are pleased to consider all qualified applicants for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, protected veterans status, Aboriginal/Native American status or any other legally-protected factors. Disability-related accommodations during the application process are available upon request.

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Note: Applications will be accepted until 11:59 PM on the day prior to the application deadline date above

Inclusion and Equal Opportunity Employment

At RBC, we believe an inclusive workplace that has diverse perspectives is core to our continued growth as one of the largest and most successful banks in the world. Maintaining a workplace where our employees feel supported to perform at their best, effectively collaborate, drive innovation, and grow professionally helps to bring our Purpose to life and create value for our clients and communities. RBC strives to deliver this through policies and programs intended to foster a workplace based on respect, belonging and opportunity for all.