Staff Platform Engineer - AI/ML
RBC
Job Overview
Who's the hiring manager?
Sign up to PitchMeAI to discover the hiring manager's details for this job. We will also write them an intro email for you.

Job Description
Staff Platform Engineer - AI/ML at RBC
We’re looking for an experienced Machine Learning Platform Engineer who will bring focus and subject-matter expertise around designing and implementing machine learning infrastructure and automation tools (MLOps and DevOps). 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:
- Develops and implements innovative machine learning algorithms and models, optimizing their performance to address complex business scenarios and improve operational efficiency.
- Collaborates with cross functional teams to identify opportunities for leveraging machine learning technologies, translating business challenges into technical solutions, and presenting findings to diverse audiences.
- Conducts and oversees state of the art research in machine learning and artificial intelligence, authoring scientific papers, presenting at industry conferences, and contributing to the organization's reputation as a leader in the field.
- Executes on machine learning development tasks or projects, requiring advanced problem solving, decision making and strategic thinking with some ambiguity.
- Drives decisions on complex issues to develop clear, actionable recommendations for management, ensuring alignment on processes, tools and services with impact across other areas.
- Leverages advanced and creative skills to resolve complex machine learning development related problems, fostering cross functional collaboration to identify and implement innovative solutions.
- Leads and facilitates cross functional collaboration efforts, fostering strong internal relationships across the organization and external partnerships to achieve impactful business outcomes.
You're our ideal candidate if you have:
- Strong and relevant experience designing and implementing distributed systems and Machine Learning 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;
- In-depth knowledge of various stages of the machine learning application deployment process;
- Experience with building tools and applications to automate various infrastructure and DevOps tasks;
- Proficiency with programming languages such as Python, Bash, or JavaScript;
- Solid understanding of the UNIX operating system;
- Implementing monitoring solutions to identify system bottlenecks and production issues;
- Knowledge of professional software engineering best practices for the full software development life cycle, including testing methods, coding standards, code reviews and source control management;
- Hands-on experience building and deploying hybrid environments on-prem and major cloud environments, such as AWS and Azure;
- Familiarity with machine learning frameworks such as PyTorch, TensorFlow and/or similar.
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.
Key skills/competency
- Machine Learning
- AI Platform Engineering
- MLOps & DevOps
- Distributed Systems
- Python Programming
- Cloud Computing (AWS, Azure)
- Data Science
- Software Development Lifecycle
- ML Orchestration
- System Monitoring
How to Get Hired at RBC
- Research RBC's AI vision: Study rbcborealis.com to understand their mission, values, recent research, and contributions to AI innovation.
- Tailor your resume: Highlight extensive experience in ML platform engineering, MLOps, DevOps, and distributed systems, specifically mentioning relevant tools and cloud platforms.
- Showcase technical projects: Prepare to discuss past projects demonstrating proficiency in Python, Bash, cloud environments (AWS/Azure), and MLOps orchestration tools like AirFlow or KubeFlow.
- Prepare for MLOps questions: Expect in-depth inquiries on designing, implementing, and monitoring ML application deployments, CI/CD pipelines, and software engineering best practices for AI/ML.
- Understand RBC's culture: Emphasize your ability to foster cross-functional collaboration, resolve complex problems creatively, and contribute to scientific advancements in the financial industry.
Frequently Asked Questions
Find answers to common questions about this job opportunity
Explore similar opportunities that match your background